Method and apparatus for performing object detection based on clutter estimation and removal in a wireless communication system

Abstract

The present disclosure relates to wireless communication technology. The present disclosure relates to a 5G communication system or a 6G communication system for supporting higher data rates beyond a 4G communication system such as Long Term Evolution (LTE). Specifically, embodiments of the present disclosure provide a first node in a wireless communication system and a method performed by said first node, said method proposing a new clutter removal solution, comprising the steps of: transmitting a first signal, receiving an echo signal of the first signal, and performing channel estimation based on the echo signal to obtain at least two groups of first channel estimation results obtained by splitting the channel estimation results or splitting the echo signal; obtaining a first clutter estimation result based on at least two groups of first channel estimation results; and performing clutter removal on at least two groups of first channel estimation results based on the first clutter estimation result to obtain a second channel estimation result. An embodiment of the present disclosure can obtain a clutter estimation result based on a grouped channel estimation result and then perform clutter removal, thereby effectively reducing the delay and computational complexity of clutter estimation and improving the efficiency of clutter estimation.

Description

Technology Field

[0001] The present disclosure generally relates to the field of wireless communication technology. More specifically, the present disclosure relates to a method and apparatus for performing detection based on clutter estimation and removal in a wireless communication system. Background Technology

[0002] Looking back at the evolution of wireless communication through successive generations, technologies have been developed primarily for human-oriented services, such as voice, multimedia, and data. Following the commercialization of 5G (5th Generation) communication systems, connected devices, which have been increasing explosively, are expected to be connected to communication networks. Examples of networked objects include vehicles, robots, drones, home appliances, displays, smart sensors installed in various infrastructures, construction machinery, and factory equipment. Mobile devices are expected to evolve into various form factors, such as augmented reality glasses, virtual reality headsets, and holographic devices. In the 6G (6th Generation) era, efforts are underway to develop improved 6G communication systems to connect hundreds of billions of devices and objects to provide diverse services. For this reason, 6G communication systems are being referred to as "beyond 5G" systems.

[0003] In the 6G communication system predicted to be realized around 2030, the maximum transmission speed is tera (i.e., 1,000 gigabit) bps (bit per second), and the wireless latency is 100 microseconds (μsec). In other words, compared to the 5G communication system, the transmission speed in the 6G communication system is 50 times faster, and the wireless latency is reduced to one-tenth.

[0004] To achieve such high data transmission speeds and ultra-low latency, 6G communication systems are being considered for implementation in the terahertz (THz) band (e.g., the 95 gigahertz (GHz) to 3 terahertz (3THz) band). Due to more severe path loss and atmospheric absorption phenomena compared to the millimeter wave (mmWave) band introduced in 5G, the importance of technologies capable of guaranteeing signal reach, or coverage, is expected to increase in the terahertz band. As key technologies to ensure coverage, new waveforms, beamforming, and multi-antenna transmission technologies such as massive Multiple-Input and Multiple-Output (MIMO), Full Dimensional MIMO (FD-MIMO), array antennas, and large-scale antennas, which are superior in terms of coverage compared to RF (Radio Frequency) devices, antennas, and OFDM (Orthogonal Frequency Division Multiplexing), must be developed. In addition, new technologies such as metamaterial-based lenses and antennas, high-dimensional spatial multiplexing technology using Orbital Angular Momentum (OAM), and Reconfigurable Intelligent Surface (RIS) are being discussed to improve the coverage of terahertz band signals.

[0005] In addition, to improve frequency efficiency and system network, development is underway in 6G communication systems for full duplex technology, in which uplink and downlink simultaneously utilize the same frequency resources at the same time; network technology that integrates satellites and HAPS (High-Altitude Platform Stations); network structure innovation technology that supports mobile base stations and enables network operation optimization and automation; dynamic spectrum sharing technology through collision avoidance based on spectrum usage prediction; AI-based communication technology that utilizes AI (Artificial Intelligence) from the design stage and internalizes end-to-end AI support functions to realize system optimization; and next-generation distributed computing technology that realizes services of complexity exceeding the limits of terminal computing capabilities by utilizing ultra-high performance communication and computing resources (Mobile Edge Computing (MEC), cloud, etc.). In addition, attempts are continuing to further strengthen connectivity between devices, further optimize networks, promote the softwareization of network entities, and increase the openness of wireless communication through the design of new protocols to be used in 6G communication systems, the implementation of hardware-based security environments, the development of mechanisms for the safe utilization of data, and the development of technologies regarding privacy maintenance methods.

[0006] Due to the research and development of such 6G communication systems, it is expected that a new dimension of hyper-connected experience will become possible through the hyper-connectivity of 6G communication systems, which encompasses not only connections between objects but also connections between people and objects. Specifically, it is projected that 6G communication systems will enable the provision of services such as truly immersive eXtended Reality (XR), high-fidelity mobile holograms, and digital replicas. Furthermore, services such as remote surgery, industrial automation, and emergency response, which are provided through 6G communication systems with enhanced security and reliability, will be applied in various fields including industry, healthcare, automotive, and home appliances. The problem to be solved

[0007] The present disclosure relates to a method and apparatus for performing detection based on clutter estimation and removal in a wireless communication system. means of solving the problem

[0008] The object of the embodiments of the present disclosure is to provide a solution for reducing computational complexity, and to achieve this object, the embodiments of the present disclosure provide a method performed by a first node in a communication system, a first node, and a readable storage medium, which are specifically described as follows.

[0009] In one embodiment, an embodiment of the present disclosure provides a method performed by a first node in a communication system, the method comprising the following steps:

[0010] A step of transmitting a first signal, receiving an echo signal of the first signal, and performing channel estimation based on the echo signal to obtain at least two groups of first channel estimation results;

[0011] A step of obtaining a first clutter estimation result based on the first channel estimation results of at least two groups; and

[0012] A step of obtaining a second channel estimation result by performing clutter removal on the first channel estimation results of at least two groups based on the first clutter estimation result.

[0013] The first channel estimation results of at least two groups are obtained by at least one of the following operations:

[0014] The operation of performing channel estimation on the above echo signal to obtain a third channel estimation result, dividing at least one third channel estimation result obtained at intervals of a preset interval value among the third channel estimation results into the same group, and obtaining at least two groups of first channel estimation results obtained by dividing the channel estimation results; and

[0015] An operation of dividing at least one echo signal obtained at intervals of the preset interval value among the echo signals into the same group to obtain at least two groups of echo signals, and performing channel estimation on the at least two groups of echo signals to obtain at least two groups of first channel estimation results obtained by dividing the echo signals.

[0016] In a possible embodiment, the interval value is determined based on the Doppler frequency distribution of non-target objects.

[0017] In a possible embodiment, if the method determines to perform clutter estimation based on the second channel estimation result, it further comprises the step of performing at least one of the following:

[0018] Performing clutter estimation based on at least one of a first signal and a third channel estimation result to obtain a second clutter estimation result, and performing clutter removal on the third channel estimation result based on the second clutter estimation result to obtain a fourth channel estimation result, thereby performing target detection based on at least one of the second channel estimation result and the fourth channel estimation result; and

[0019] A third clutter estimation result is obtained by performing clutter estimation based on at least one of at least two groups of first channel estimation results obtained by splitting the first signal and the echo signal, and a fifth channel estimation result is obtained by performing clutter removal on at least two groups of first channel estimation results obtained by splitting the echo signal based on the third clutter estimation result, thereby performing target detection based on at least one of the second channel estimation result and the fifth channel estimation result.

[0020] In a possible embodiment, the step of performing clutter estimation based on at least one of the first signal and the third channel estimation result to obtain a second clutter estimation result, and performing clutter removal on the third channel estimation result based on the second clutter estimation result to obtain a fourth channel estimation result, comprises the following:

[0021] A step of constructing a first matrix of a clutter subspace based on at least one of the frequency domain signal of the first signal and the third channel estimation result;

[0022] A step of obtaining a reconstructed second clutter estimation result by performing signal reconstruction based on the first matrix and the third channel estimation result; and

[0023] A step of obtaining a fourth channel estimation result by performing clutter removal on the third channel estimation result based on the second clutter estimation result; and

[0024] The step of obtaining a third clutter estimation result by performing clutter estimation based on at least one of at least two groups of first channel estimation results obtained by splitting the first signal and the echo signal, and obtaining a fifth channel estimation result by performing clutter removal on at least two groups of first channel estimation results obtained by splitting the echo signal based on the third clutter estimation result, comprises the following:

[0025] A step of constructing a second matrix of the clutter subspace based on at least one of at least two groups of first channel estimation results obtained by splitting the frequency domain signal of the first signal and the echo signal;

[0026] A step of performing signal reconstruction based on at least two groups of first channel estimation results obtained by the second matrix and the division of the echo signal, thereby obtaining a reconstructed third clutter estimation result; and

[0027] A step of obtaining the fifth channel estimation result by performing clutter removal on at least two groups of first channel estimation results obtained by splitting the echo signal based on the third clutter estimation result.

[0028] In possible embodiments, the method further comprises the following:

[0029] A step of determining whether target detection based on the fourth channel estimation result or the fifth channel estimation result satisfies the first condition;

[0030] When the first condition is satisfied, a step of constructing a third matrix of the clutter subspace based on the result of the target detection;

[0031] A step of obtaining a reconstructed fourth clutter estimation result by performing signal reconstruction based on the third matrix and the third channel estimation result; or obtaining a fifth clutter estimation result by performing signal reconstruction based on at least two groups of first channel estimation results obtained by the third matrix and the splitting of the echo signal; and

[0032] A step of obtaining a sixth channel estimation result by performing clutter removal on the third channel estimation result based on the fourth clutter estimation result; or obtaining a seventh channel estimation result by performing clutter removal on at least two groups of first channel estimation results obtained by splitting the echo signal based on the fifth clutter estimation result.

[0033] The above first condition includes at least one of the following:

[0034] The power of the fourth channel estimation result or the fifth channel estimation result of the target object is detected to be greater than the power of the noise floor, and the detected Doppler frequency of the target object is not equal to zero;

[0035] The power of the fourth channel estimation result or the fifth channel estimation result of the target object is detected to be greater than the power of the noise floor, and the detected Doppler frequency of the target object is an integer multiple of the non-zero Doppler resolution;

[0036] The power of the fourth channel estimation result or the fifth channel estimation result of a target object corresponding to at least one of a preset distance and a preset angle is detected to be greater than the power of the noise floor, and the detected Doppler frequency of the target object is not equal to 0; and

[0037] The power of the fourth channel estimation result or the fifth channel estimation result of a target object corresponding to at least one of the above preset distance and preset angle is detected to be greater than the power of the noise floor, and the detected Doppler frequency of the target object is an integer multiple of the non-zero Doppler resolution.

[0038] In a possible embodiment, deciding to perform clutter estimation based on the second channel estimation result includes the following:

[0039] Determining whether the above second channel estimation result satisfies a preset second condition;

[0040] Deciding to perform clutter estimation if the second channel estimation result satisfies the second condition; and

[0041] If the second channel estimation result does not satisfy the second condition, performing target detection based on the second channel estimation result.

[0042] The above second condition includes at least one of the following:

[0043] The power of the noise floor of the second channel estimation result is greater than or equal to a preset threshold;

[0044] The power of the channel estimation result corresponding to the zero Doppler frequency within the second channel estimation result is greater than or equal to the preset threshold value;

[0045] The power of the noise floor corresponding to at least one of the preset distance and preset angle in the second channel estimation result is greater than or equal to the preset threshold; and

[0046] The power of the channel estimation result corresponding to the zero Doppler frequency corresponding to at least one of the preset distance and preset angle within the second channel estimation result is greater than or equal to the preset threshold value.

[0047] In a possible embodiment, the preset threshold is related to the distance of the detected target object and / or the radar cross section (RCS) of the target object.

[0048] In another aspect, an embodiment of the present disclosure provides a first node in a wireless communication system, said node includes a transceiver, and at least one processor is connected to said transceiver, said at least one processor is configured to perform a method provided by any one of the embodiments of the present disclosure.

[0049] In another aspect, an embodiment of the present disclosure also provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, it performs the method provided by any one of the embodiments of the present disclosure.

[0050] In another aspect, a computer program product is provided that includes a computer program performing a method provided in any one of the optional embodiments of the present disclosure when executed by a processor.

[0051] The beneficial effects provided by the embodiments of the present disclosure will be described below in conjunction with specific embodiments. Effects of the invention

[0052] An embodiment of the present disclosure provides an efficient communication method in a wireless communication system. Brief explanation of the drawing

[0053] FIG. 1 illustrates a structural diagram of a wireless network system to which an embodiment of the present disclosure can be applied. FIG. 2 illustrates a structural diagram of an exemplary base station according to the present disclosure. FIG. 3 illustrates a structural diagram of an exemplary user terminal according to the present disclosure. FIG. 4 illustrates a flowchart of a method performed by a first node provided by an embodiment of the present disclosure. FIG. 5 illustrates a flowchart of a method for clutter estimation and clutter removal according to an embodiment of the present disclosure. FIG. 6 illustrates a flowchart of a method for estimating a first clutter according to an embodiment of the present disclosure. FIG. 7 illustrates a diagram grouping channel estimation results according to an embodiment of the present disclosure. FIG. 8 illustrates a flowchart of a method for removing clutter according to an embodiment of the present disclosure. FIG. 9 illustrates a diagram arranging channel estimation results according to an embodiment of the present disclosure. FIG. 10 illustrates a flowchart of another method for clutter estimation and clutter removal according to an embodiment of the present disclosure. FIG. 11 illustrates a flowchart of a method for dynamically determining whether to perform clutter estimation and clutter removal according to an embodiment of the present disclosure. FIG. 12 illustrates a structural diagram of an electronic device according to an embodiment of the present disclosure. FIG. 13 illustrates the configuration of a UE in a wireless communication system according to various embodiments. FIG. 14 illustrates the configuration of a base station or network entity in a wireless communication system according to various embodiments. It should be noted that throughout the drawing, similar reference numerals are used to depict identical or similar elements, features, and structures. Specific details for implementing the invention

[0054] Before reviewing the modes of the invention below, it may be advantageous to define specific words and phrases used throughout this patent document.

[0055] The term "connect" and its derivatives refer to any direct or indirect communication between two or more elements, regardless of whether the two or more elements are in physical contact with each other.

[0056] The terms "transmit," "receive," and "communicate," and their derivatives, include both direct and indirect communication.

[0057] The terms "equip" and "include" and their derivatives mean including without restriction.

[0058] The term "or" is comprehensive, meaning and / or.

[0059] The phrase "associated" and its derivatives mean including, being included, interconnected, accommodating, being accommodated, being connected, being linked, communicating, cooperating, being inserted, being juxtaposed, being close, being bound, having, possessing attributes, forming a relationship, etc.

[0060] The term "controller" means any device, system, or part thereof that controls at least one operation. Such a controller may be implemented in hardware or as a combination of hardware, software, and / or firmware. Functions associated with any particular controller may be centralized or distributed, whether local or remote.

[0061] When used with a list of items, the phrase "at least one" means that different combinations of one or more of the listed items may be used, or that only one item within the list may be required. For example, "at least one of A, B, and C" includes any of the following combinations: namely, A; B; C; A and B; A and C; B and C; or A, B, and C. Likewise, the term "set" implies one or more. Therefore, a set of items may be a single item or a collection of two or more items.

[0062] The singular forms "a," "an," and "the" should be understood to include plural references unless the context clearly indicates otherwise. Thus, for example, a reference to "component surfaces" includes a reference to one or more such surfaces.

[0063] Additionally, the various functions described below may be implemented or supported by one or more computer programs, each of which is formed of computer-readable program code and implemented on a computer-readable medium. The terms “application” and “program” refer to one or more computer programs, software components, instruction sets, procedures, functions, objects, classes, instances, related data, or parts thereof adapted to be implemented by appropriate computer-readable program code. The phrase “computer-readable program code” includes any type of computer code, including source code, object code, and executable code. The phrase “computer-readable medium” includes any type of medium accessible by a computer, such as read-only memory (ROM), random access memory (RAM), hard disk drives, compact discs (CDs), digital video discs (DVDs), or any other type of memory. “Non-transient” computer-readable medium excludes wired, wireless, optical, or other communication links that transmit transient electrical or other signals. Non-transient computer-readable media include media in which data can be permanently stored, and media in which data can be stored and later overwritten, such as rewritable optical discs or erasable memory devices.

[0064] Definitions for other specific words and phrases are provided throughout this disclosure. A person skilled in the art should understand that, in most, if not most, cases, these definitions apply to the prior use as well as the future use of such defined words and phrases.

[0065] The drawings incorporated herein and the various embodiments used to illustrate the principles of the present disclosure are for illustrative purposes only and should not be construed as limiting the scope of the present disclosure in any way. Furthermore, those skilled in the art will understand that the principles of the present disclosure may be implemented in any appropriately arranged wireless communication system.

[0066] FIGS. 1 through 3 below illustrate various embodiments of the present disclosure implemented in a wireless communication system. The description in FIGS. 1 through 3 does not imply any physical or structural limitations on the manner in which different embodiments may be implemented. Various embodiments of the present disclosure may be implemented in any communication system appropriately configured.

[0067] FIG. 1 illustrates an exemplary wireless network according to an embodiment of the present disclosure. The embodiment of the wireless network shown in FIG. 1 is for illustrative purposes only. Other embodiments of the wireless network (100) may be used without departing from the scope of the present disclosure.

[0068] As illustrated in FIG. 1, the wireless network includes a base station (gNB or gNodeB) (101), a gNB (102), and a gNB (103). The gNB (101) communicates with the gNB (102) and the gNB (103). The gNB (101) also communicates with at least one network (130), such as the Internet, a proprietary Internet Protocol (IP) network, or another data network.

[0069] The gNB (102) provides wireless broadband access to the network (130) to a first plurality of user terminals (UE) within the coverage area (120) of the gNB (102). The first plurality of UEs include a UE (111) that may be located in a small business; a UE (112) that may be located in a business (E); a UE (113) that may be located in a WiFi hotspot (HS); a UE (114) that may be located in a first residence (R1); a UE (115) that may be located in a second residence (R2); and a UE (116) that may be a mobile device (M) such as a cell phone, a wireless laptop, a wireless PDA (personal digital assistant), etc. The gNB (103) provides wireless broadband access to the network (130) to a second plurality of UEs within the coverage area (125) of the gNB (103). The second plurality of UEs includes UE (115) and UE (116), and subscriber stations (SS, e.g., UEs) (117, 118, and 119). In some embodiments, one or more gNBs (101 to 103) may communicate with each other using conventional wireless communication technology and may also communicate with UEs (111 to 116), and one or more UEs (111 to 119) may communicate directly with each other (e.g., UEs (117 to 119)) using other conventional or proposed wireless communication technology.

[0070] Depending on the network type, the terms “base station” or “BS” may refer to any component (or a set of components) configured to provide wireless access to a network, such as a transmitting point (TP), a transmitting-receiving point (TRP), an enhanced (or “evolved”) base station (eNodeB or eNB), a 5G base station (gNB), a macrocell, a femtocell, a WiFi access point (AP), or other wireless-enabled devices. A base station may provide wireless access according to one or more wireless communication protocols, such as 3GPP 5G New Radio (NR), LTE (Long Term Evolution), LTE-A (LTE Advanced), HSPA (high speed packet access), Wi-Fi 802.11a / b / g / n / ac, etc. For convenience, various names for base station type devices and functions are used interchangeably in this patent document to refer to network infrastructure components that provide wireless access to remote terminals. Additionally, depending on the network type, the term "User Terminal (UE)" may refer to any component such as a Mobile Station (MS), Subscriber Station (SS), Remote Terminal, Wireless Terminal, Receiver Point, or User Device. For convenience, various names for User Terminal type devices and functions are used interchangeably in this patent document to refer to a remote wireless terminal wirelessly accessing a BS, whether the UE is considered a mobile device (e.g., a mobile phone or smartphone) or a fixed device (e.g., a desktop computer or keyboard).

[0071] The dotted lines indicate the approximate range of the coverage areas (120 and 125), and these areas are depicted as roughly circular for illustrative and explanatory purposes only. It should be clearly understood that coverage areas associated with a gNB, such as coverage areas (120 and 125), may have different shapes, including irregular shapes, depending on the configuration of the gNB and changes in the wireless environment associated with natural and artificial obstacles.

[0072] As described in more detail below, one or more UEs (111 to 119) include circuits, programming, or a combination thereof. In certain embodiments, one or more BSs (101 to 103) include circuits, programming, or a combination thereof.

[0073] FIG. 1 illustrates an example of a wireless network, but various modifications to FIG. 1 may be made. For example, the wireless network (100) may include any number of gNBs and any number of UEs in any suitable arrangement. Additionally, the gNB (101) may communicate directly with any number of UEs and provide such UEs with wireless broadband access to the network (130). Similarly, each gNB (102 to 103) may communicate directly with the network (130) and provide UEs with direct wireless broadband access to the network (130). Additionally, the gNBs (101, 102 and / or 103) may provide access to other or additional external networks, for example, an external telephone network or other types of data networks.

[0074] FIG. 2 illustrates an exemplary base station according to an embodiment of the present disclosure. The embodiment of the gNB (102) illustrated in FIG. 2 is for illustrative purposes only, and the gNB (101 and 103) of FIG. 1 may have the same or similar configuration. However, gNBs are provided in a wide variety of configurations, and FIG. 2 does not limit the scope of the present disclosure to any specific embodiment of the gNB.

[0075] As illustrated in FIG. 2, the gNB (102) includes a plurality of antennas (200a to 200n), a plurality of radio frequency (RF) transceivers (201a to 201n), a transmit (TX) processing circuit (203), and a receive (RX) processing circuit (204). The gNB (102) also includes a controller / processor (205), a memory (206), and a backhaul or network interface (207).

[0076] RF transceivers (201a to 201n) receive an incoming RF signal from an antenna (200a to 200n), such as a signal transmitted by a UE in the network (100). The RF transceivers (201a to 201n) down-convert the incoming RF signal to generate an intermediate frequency (IF) or baseband signal. The IF or baseband signal is transmitted to an RX processing circuit (204), and the RX processing circuit (204) generates a processed baseband signal by filtering, decoding, and / or digitizing the baseband or IF signal. The RX processing circuit (204) transmits the processed baseband signal to a controller / processor (205) for further processing.

[0077] The TX processing circuit (203) receives analog or digital data (e.g., voice data, web data, email, or interactive video game data) from the controller / processor (205). The TX processing circuit (203) encodes, multiplexes, and / or digitizes the outgoing baseband data to generate a processed baseband or IF signal. RF transceivers (201a to 201n) receive the outgoing processed baseband or IF signal from the TX processing circuit (203) and up-convert the baseband or IF signal into an RF signal transmitted through the antennas (201a to 201n).

[0078] The controller / processor (205) may include one or more processors or other processing units that control the overall operation of the gNB (102). For example, the controller / processor (205) may control the reception of forward channel signals and the transmission of reverse channel signals by RF transceivers (201a to 201n), an RX processing circuit (204), and a TX processing circuit (203) according to well-known principles. The controller / processor (205) may also support additional functions, such as enhanced wireless communication functions.

[0079] For example, the controller / processor (205) can support beamforming or directional routing operations that effectively steer outgoing signals in a desired direction by weighting outgoing signals from multiple antennas (200a to 200n) differently. The controller / processor (205) can support any of the various other functions in the gNB (102).

[0080] The controller / processor (205) can also execute programs and other processes residing in memory (206), such as an operating system (OS). The controller / processor (205) can move data into or out of memory (206) as required by the execution process.

[0081] The controller / processor (205) is also connected to a backhaul or network interface (207). The backhaul or network interface (207) enables the gNB (102) to communicate with other devices or systems via a backhaul connection or network. The interface (207) may support communication via any suitable wired or wireless connection(s). For example, when the gNB (102) is implemented as part of a cellular communication system (e.g., a system supporting 5G, LTE, or LTE-A), the interface (207) may enable the gNB (102) to communicate with other gNBs via a wired or wireless backhaul connection. When the gNB (102) is implemented as an access point, the interface (207) may enable the gNB (102) to communicate with a large network (e.g., the Internet) via a wired or wireless local area network or via a wired or wireless connection. The interface (207) includes any suitable structure that supports communication via wired or wireless connection, such as Ethernet or RF transceivers.

[0082] The memory (206) is connected to the controller / processor (205). Part of the memory (206) may include random access memory (RAM), and other parts of the memory (206) may include flash memory or other read-only memory (ROM).

[0083] FIG. 2 illustrates an example of a gNB (102), but various modifications can be made to FIG. 2. For example, the gNB (102) may include any number of each component shown in FIG. 2. As a specific example, the access point may include multiple interfaces (207), and the controller / processor (205) may support a routing function for routing data between different network addresses. As another specific example, although it is illustrated as including a single instance of the TX processing circuit (203) and a single instance of the RX processing circuit (204), the gNB (102) may include multiple instances of each (e.g., one per RF transceiver). Additionally, the various components of FIG. 2 may be combined, further subdivided, or omitted, and additional components may be added as needed.

[0084] FIG. 3 illustrates an exemplary user terminal according to an embodiment of the present disclosure. The embodiment of the UE (116) illustrated in FIG. 3 is for illustrative purposes only, and the UEs of FIG. 1 (111 to 115, and 117 to 119) may have the same or similar configurations. However, the UE is provided in a wide variety of configurations, and FIG. 3 does not limit the scope of the present disclosure to any specific embodiment of the UE.

[0085] As illustrated in FIG. 3, the UE (116) includes an antenna (301), a radio frequency (RF) transceiver (302), a TX processing circuit (303), a microphone (304), and a receive (RX) processing circuit (305). The UE (116) also includes a speaker (306), a controller or processor (307), an input / output (I / O) interface (IF) (308), an input device (309), a touchscreen display (310), and a memory (311). The memory (311) includes an OS (312) and one or more applications (313).

[0086] The RF transceiver (302) receives an incoming RF signal transmitted by the gNB of the network (100) from the antenna (301). The RF transceiver (302) down-converts the incoming RF signal to generate an IF or baseband signal. The IF or baseband signal is transmitted to an RX processing circuit (305), and the RX processing circuit (305) generates a processed baseband signal by filtering, decoding, and / or digitizing the baseband or IF signal. The RX processing circuit (305) transmits the processed baseband signal to a speaker (306) (e.g., for voice data) or to a processor (307) for further processing (e.g., for web browsing data).

[0087] The TX processing circuit (303) receives analog or digital voice data from the microphone (304) or other outgoing baseband data (such as web data, email, or interactive video game data) from the processor (307). The TX processing circuit (303) encodes, multiplexes, and / or digitizes the outgoing baseband data to generate a processed baseband or IF signal. The RF transceiver (302) receives the outgoing processed baseband or IF signal from the TX processing circuit (303) and upconverts the baseband or IF signal into an RF signal transmitted through the antenna (301).

[0088] The processor (307) may include one or more processors or other processing units and may execute an OS (312) stored in memory (311) to control the overall operation of the UE (116). For example, the processor (307) may control the reception of a forward channel signal and the transmission of a reverse channel signal by an RF transceiver (302), an RX processing circuit (305), and a TX processing circuit (303) according to well-known principles. In some embodiments, the processor (307) includes at least one microprocessor or microcontroller.

[0089] The processor (307) may also execute other processes and programs residing in memory (311), such as a process for CSI reporting on the uplink channel. The processor (307) may move data into or out of memory (311) as required by the execution process. In some embodiments, the processor (307) is configured to execute an application (313) based on the OS (312) or in response to a signal received from the gNB or operator. The processor (307) is also connected to an I / O interface (308), and the I / O interface (308) provides the UE (116) with the ability to connect to other devices, such as laptop computers and handheld computers. The I / O interface (308) is a communication path between these accessories and the processor (307).

[0090] The processor (307) is also connected to a touchscreen display (310). A user of the UE (116) can input data into the UE (116) using the touchscreen display (310). The touchscreen display (310) may be a liquid crystal display, a light-emitting diode display, or, for example, another display capable of rendering text and / or at least limited graphics from a website.

[0091] The memory (311) is connected to the processor (307). Part of the memory (311) may include RAM, and other parts of the memory (311) may include flash memory or other ROM.

[0092] FIG. 3 illustrates an example of a UE (116), but various modifications can be made to FIG. 3. For example, various components of FIG. 3 may be combined, further subdivided, or omitted, and additional components may be added as needed. As a specific example, the processor (307) may be divided into multiple processors, for example, one or more central processing units (CPUs) and one or more graphics processing units (GPUs). Also, FIG. 3 illustrates a UE (116) configured as a mobile phone or smartphone, but the UE may be configured to operate as other types of mobile or stationary devices.

[0093] With the advancement of science and technology, the diversity of communication devices is increasing. In addition to conventional devices such as mobile phones and computers, this includes mobile robots like autonomous vehicles and unmanned aerial vehicles. These types of mobile devices require or must be capable of precise position estimation to accurately identify and respond to current situations; in other words, they must possess position estimation capabilities similar to those provided by radar technology. A simple approach might be to equip communication devices with radar modules. However, as the operating frequency bands of communication systems have recently evolved to high frequencies, communication frequency bands have increasingly approached radar frequency bands. Consequently, interference and resource conflicts between communication and radar systems will become inevitable. One idea to address this issue is to consider a fusion system of communication and radar, known as Integrated Sensing and Communication (ISAC), to further enhance communication system capabilities and improve spectral efficiency. Currently, ISAC is considered one of the core technologies for future communication systems by both industry and academia.

[0094] The core approach of ISAC is to achieve the detection of the surrounding environment while consuming as few resources as possible by using the same set of hardware devices on the foundation of guaranteeing basic communication functions. That is, communication nodes within a communication system (e.g., gNBs, UEs, repeaters, and Integrated Access and Backhaul (IAB) base stations) can simultaneously possess communication and detection functions; these communication nodes may be referred to as ISAC nodes, and hereinafter referred to as communication and detection nodes. A detection function is added to the communication system, and a possible solution is for a first communication and detection node (which may also be referred to as the first node) to receive a detection signal (hereinafter referred to as the detection signal) transmitted by a second communication and detection node (which may also be referred to as the second node), and to acquire the characteristics of a detected target object based on signal detection of the said detection signal. Since the detection signal is reflected by the detected target object within the environment, the frequency response of the propagation channel changes accordingly, and this change in frequency response has a corresponding relationship with the distance and movement speed of the detected target object. Accordingly, the first communication and detection node can estimate the propagation channel based on the received echo signal and obtain the characteristics of the detected target object. The characteristics of the detected target object may include, but are not limited to, the number of detected target objects, the distance between the detected target object and the communication and detection node, and the radial speed of the detected target object; additionally, the detected target object may be an object accessing the communication network (e.g., base stations and terminals) or an object not accessing the communication network (e.g., small unmanned aerial vehicles (UAVs), buildings, animals, and plants).

[0095] In the aforementioned communication and sensing solution, the first communication and sensing node and the second communication and sensing node may be a base station and a user, respectively; for example, the first communication and sensing node may be a user terminal (UE) and the second communication and sensing node may be its serving cell, or the second communication and sensing node may be a UE and the first communication and sensing node may be its serving cell. Depending on the sensing requirements, the serving cell may be configured to allow the UE to transmit or receive a sensing signal. This may correspond to a procedure in which the UE is configured to transmit an uplink sensing signal and the base station of the serving cell receives the uplink sensing signal to perform a sensing measurement, which is referred to as uplink sensing below; furthermore, this may correspond to a procedure in which the UE is configured to receive a downlink sensing signal and perform a sensing measurement, which is referred to as downlink sensing below.

[0096] Since both the detected target object and the observation node are generally located in a ground or low-altitude environment, the detection signals received by the communication and detection nodes may be affected by clutter within that environment, which severely degrades detection performance; such clutter is caused by echoes reflected back from scatterers within the environment, such as the ground, buildings, and trees; and since the scatterers causing such clutter are generally not the target object that actually needs to be detected, such clutter becomes an interfering signal to the echoes of the target object that actually needs to be detected (e.g., people, vehicles, and drones).

[0097] For example, when communication and sensing nodes are fixed nodes (e.g., base stations), clutter interference caused by the ground and surrounding buildings becomes a significant factor affecting the system's sensing performance, particularly in the detection, positioning, and tracking of frequently mentioned "low, slow, and small" targets. In addition to the reflected signals of target objects to be detected within the environment, various types of clutter reflected from surrounding buildings and the ground exist, which will affect the detection of stationary or low-speed moving target objects. When the target object's speed is slow and the reflected energy is weak, the impact caused by the sidelobes of static clutter becomes more severe. If echoes accumulate coherently without any processing, the clutter sidelobes can become too strong to obscure the target object, significantly degrading the target object detection capability of the communication and sensing nodes. Therefore, clutter suppression is a key measure to ensure that communication and sensing nodes can detect target objects that need to be detected, and in particular, the detection of low-speed objects requires a higher capability to eliminate clutter interference.

[0098] In the prior art, a clutter suppression method can be performed based on accumulated echo data, specifically by receiving multiple echo data groups and then performing processing on the multiple echo data groups; however, since this method requires processing multiple received echo data groups, the delay in accumulating echo data is large, and the complexity of processing multiple echo data groups is also high, which has a serious impact on the efficiency of clutter estimation and object detection. Therefore, a method to effectively reduce the delay and computational complexity of clutter estimation and improve clutter estimation efficiency is a problem that needs to be urgently solved.

[0099] In the present disclosure, a detection solution (a method executed by a first node within a communication integration system) is provided to optimize an ISAC system and to solve or improve one or more existing problems, for reducing computational complexity and improving the detection capability of a target object. Additionally, the solution also proposes a clutter estimation and removal method adapted to a communication and detection node, which can adaptively determine whether to perform non-real-time or real-time clutter estimation; non-real-time estimation enables the communication and detection node to adapt to long-term changes in clutter, while real-time estimation can capture short-term changes in clutter. Specifically, in the non-real-time clutter estimation method, echoes of the environmental background (environmental clutter) are accumulated, and clutter feature extraction is performed on the accumulated echoes (see Example 2 below for details). Based on the non-real-time clutter estimation results (extracted clutter features), clutter components can be reconstructed in real time, and clutter components within the echo signal containing clutter and the target object can be effectively removed (see Example 3 below for details), thereby improving the detection performance of the target object. The real-time clutter estimation method performs clutter channel estimation in the frequency domain based on the real-time accumulated echoes, and then performs clutter reconstruction and removal in real time (see Example 4 below for details).In addition, the clutter estimation and removal method adapted to the communication and sensing nodes can adaptively determine the clutter estimation and removal method based on the first clutter removal result using non-real-time clutter estimation, which is intended to improve the detection performance of the target object. Specifically, it dynamically determines whether to detect the target object by continuously using the echo signal obtained by the first clutter removal using the non-real-time clutter estimation result, or to perform real-time clutter estimation and remove the clutter using the real-time clutter estimation result; and then, the target object detection is performed based on the first clutter removal echo signal using the real-time clutter estimation result (see Example 5 below for details). This has the advantage that by combining non-real-time clutter estimation and real-time clutter estimation, the communication and sensing nodes can obtain a more accurate clutter characteristic model with higher robustness against dynamically changing clutter scenes and environmental conditions, and achieve superior clutter removal and target object detection capabilities.

[0100] The method provided by the embodiments of the present disclosure may be performed by any electronic device / node, such as a UE in a wireless communication system, or by a network node, such as a base station or other network node.

[0101] It should be noted that some of the terms referred to in the embodiments of this disclosure may be terms already existing in communication standards, some may be newly added or newly defined terms, these terms may be referred to by other names, or may be described in a different way (e.g., text description) in future communication standards. The names or phrases of the various signals / information / matrices / spaces / results mentioned in the embodiments of this disclosure are not proprietary, and such names or phrases may theoretically be changed insofar as the role, content, or description of said signals / information / matrices / spaces / results corresponds to or is associated with one another.

[0102] The technical solution provided by the present disclosure and the technical effect induced by the technical solution are described below through the description of various optional embodiments. Unless there is a conflict or contradiction, the following embodiments may be referenced, learned from, or combined with one another, and descriptions of the same terms, similar features, and similar steps in different embodiments will not be repeated. In embodiments comprising multiple steps, the embodiments of the present disclosure do not exclusively limit the order in which the multiple steps are performed, unless there is an explicit order for the multiple steps.

[0103] Optional embodiments of the method provided by the present disclosure will be further described below in relation to the principles of the solution provided by the present disclosure and several optional embodiments, and the steps of different embodiments may be combined or substituted with one another where there is no conflict.

[0104] FIG. 4 illustrates a method performed by a first node in a wireless communication system according to an embodiment of the present disclosure, wherein the method is a clutter estimation method. The first node is a sensing node, optionally, the first node may be a UE, and the first node may be a base station in the communication system, etc.; as illustrated in FIG. 4, the method may include S101 to S104:

[0105] According to an embodiment of the present disclosure, in step S101, the method comprises the steps of transmitting a first signal, receiving an echo signal of the first signal, and performing channel estimation based on the echo signal to obtain at least two groups of first channel estimation results.

[0106] According to an embodiment of the present disclosure, in step S102, the method includes the step of obtaining a first clutter estimation result based on at least two groups of first channel estimation results.

[0107] According to an embodiment of the present disclosure, in step S103, the method comprises the step of obtaining a second channel estimation result by performing clutter removal on at least two groups of first channel estimation results based on a first clutter estimation result.

[0108] According to an embodiment of the present disclosure, at least two groups of first channel estimation results can be obtained by at least one of the following operations A1-A2:

[0109] A1: An operation of performing channel estimation on an echo signal to obtain a third channel estimation result, dividing at least one third channel estimation result obtained at intervals of a preset interval value among the third channel estimation results into the same group, and obtaining at least two groups of first channel estimation results obtained by dividing the channel estimation results.

[0110] A2: An operation of dividing at least one echo signal obtained at intervals of the preset interval value among the echo signals into the same group to obtain at least two groups of echo signals, and performing channel estimation on the at least two groups of echo signals to obtain at least two groups of first channel estimation results obtained by dividing the echo signals.

[0111] Optionally, the first signal may be a signal transmitted by the first node to the second node. For example, the first node may transmit the first signal to the second node, and the second node may transmit the second signal to the first node. In the field of communication and sensing, the first signal and the second signal may be referred to as sensing signals and may include signals transmitted for sensing; accordingly, the first node and the second node may be communication and sensing nodes (sometimes referred to as sensing nodes). After transmitting the sensing signal, the sensing node receives the echo signal of the sensing signal Can receive, where a positive integer is the number of echoes received by the sensing node, and is a positive integer is the number of sampling points of a single echo.

[0112] Optionally, when channel estimation is performed based on echo signals, channel estimation can be performed directly on the echo signals, or the echo signals can be grouped first, and then channel estimation can be performed on at least two groups of echo signals obtained after grouping.

[0113] The following is a description of how to obtain first-channel estimation results for at least two groups.

[0114] In one possible embodiment, the channel estimation results are grouped to obtain at least two groups of first channel estimation results obtained by splitting the channel estimation results. Specifically, a third channel estimation result is obtained by performing channel estimation on an echo signal, and at least one third channel estimation result obtained at intervals of a preset interval value among the third channel estimation results is split into the same group to obtain at least two groups of first channel estimation results obtained by splitting the channel estimation results.

[0115] Acquired Channel estimation is performed on the echo signals to obtain the third channel estimation result. ...can be obtained. Here, the number of echo signals is equal to the number of third channel estimation results; that is, it can be understood that one third channel estimation result can be obtained by performing channel estimation on one echo signal. Optionally, one embodiment for obtaining the third channel estimation result is the echo signal of the first signal. Time-domain representation of the echo signal by performing a Discrete Fourier Transform (DFT) on it The third channel estimation result is obtained by obtaining and then performing channel estimation using the least squares (LS) method. It may be acquiring, and here is a reference signal.

[0116] The detection node estimates the third channel result based on a preset interval value By grouping, at least two groups of first channel estimation results can be obtained; for example, when the interval value is 4, one or more third channel estimation results are obtained for every interval of four third channel estimation results, and then divided into the same group to obtain at least two groups of first channel estimation results.

[0117] Optionally, the interval value can be equal to the number of groups, for example, Includes dog echoes, that is, Includes three third-channel estimation results, is the interval value, and the number of third-channel estimation results within each group is And, the number of frequency domain sampling points within each group is is. The first channel estimation results of at least two groups This can be obtained by grouping the third channel estimation results.

[0118] Optionally, For the third channel estimation results, each For each of the channel estimation results, at least one third channel estimation result can be selected and grouped into the same group, and the third channel estimation result After grouping, the first channel estimation results of at least two groups You can obtain.

[0119] Optionally, one possible grouping method is illustrated in FIG. 7, wherein the index of the third channel estimation result for the received echo signal of the first signal is {1, 2, ..., Np}, the set of indices of the echo signals constituting the channel estimation result of the first group is And, the set of indexes of echo signals constituting the channel estimation result of the second group is and, in this way, my The set of indexes of echo signals constituting the group's channel estimation results is am.

[0120] The value of is a positive integer greater than 1, and It is a divisor of. It should be noted that the advantage of grouping channel estimation results is that, through the grouping mentioned above, all major frequency domain characteristics of the clutter, such as the Doppler frequency shift characteristics of the clutter included in the channel estimation results of each group, can be preserved, and the frequency domain characteristics of the clutter within the channel estimation results of each group are similar to one another; furthermore, it should be noted that the accuracy of clutter feature analysis can be improved by performing feature analysis on the channel estimation results of multiple groups. Also, the interval value The value depends on the distribution of the clutter velocity (Doppler frequency shift) within the environment, and if the clutter velocity is faster or the proportion of high-speed clutter in the clutter velocity distribution within the environment is high, in order to ensure that the Doppler characteristics of the clutter are not lost in the channel estimation results of each group (i.e., to ensure that high-speed clutter can be reflected in the channel estimation results of each group), the first channel estimation result for the received echo signal of the first signal A narrower gap from You must select one, two, or more channel estimation results and split them into the same group; accordingly, the number of channel estimation results within each group increases, and the interval value becomes smaller. For example, with respect to the detection node, if the velocity distribution of clutter within the current detection scene is concentrated at zero (0) velocity, the interval value You can select a larger value for; and for the detection node, if the velocity distribution of clutter within the current detection scene is mainly high, the interval value You can choose a smaller value. The advantage of this is, By flexibly adjusting it, it is possible to ensure that channel estimation results of multiple groups can be obtained without loss of clutter velocity information from the channel estimation results of each group. Clutter feature extraction based on channel estimation results of multiple groups can effectively reduce the influence of noise and improve the accuracy of clutter feature extraction.

[0121] Optionally, when grouping third channel estimation results based on a preset interval value, the number of groups obtained by splitting is related to the number of channel estimation results obtained consecutively at that interval. In one example, the first channel estimation results of each group may include different third channel estimation results obtained at that interval, and these may take the form of consecutive third channel estimation results. In one example, the same third channel estimation result may be split into first channel estimation results of different groups, for example, when grouping, the first channel estimation result of one group includes the same third channel estimation result as the first channel estimation result of another group.

[0122] For example, assuming there are 10 echo signals (correspondingly, 10 third-channel estimation results) and an interval value of 5, if one third-channel estimation result is obtained and grouped for every 5 intervals of third-channel estimation results, the number of groups is set to be equal to the interval value, so that 5 groups of first-channel estimation results can be obtained; if two or more third-channel estimation results are obtained and grouped for every 5 intervals of third-channel estimation results, while maintaining the number of groups equal to the interval value, the channel estimation results of different groups will contain the same third-channel estimation result, that is, one third-channel estimation result will be repeatedly sampled and divided into different groups; if two or more third-channel estimation results are obtained and grouped for every 5 intervals of third-channel estimation results, the set number of groups can be related to the number of two or more third-channel estimation results obtained for that interval, and in this case, they can be arranged to group the same third-channel estimation results without repeated sampling.

[0123] In one possible embodiment, the echo signal is grouped to obtain at least two groups of first channel estimation results obtained by splitting the echo signal. Specifically, at least one echo signal obtained at intervals of interval values ​​among the echo signals is split into the same group to obtain at least two groups of echo signals, and channel estimation is performed on the at least two groups of echo signals to obtain at least two groups of first channel estimation results obtained by splitting the echo signal.

[0124] The detection node is acquired based on a preset interval value By grouping the echo signals, at least two groups of grouped echo signals can be obtained; for example, when the interval value is 5, at least one echo signal can be obtained for every interval of 5 echo signals and divided into the same group, thereby obtaining at least two groups of echo signals.

[0125] Optionally, the interval value can be equal to the number of groups, for example, Includes dog echoes, is the interval value, and the number of echo signals within each group is and the number of frequency domain sampling points within each group is am.

[0126] Optionally, given a possible grouping approach, the index of the received echo signal of the first signal is {1,2,… , N p If}, the index set of echo signals constituting the first group is and the index set of echo signals constituting the second group is , and continuously, my The index set of echo signals constituting the group is am.

[0127] The value of is a positive integer greater than 1, and It is a divisor of. It should be noted that the advantage of grouping echo signals is that, through the grouping mentioned above, all major frequency domain characteristics of the clutter, such as the Doppler frequency shift characteristics of the clutter contained in each group's echo signal, can be preserved, and the frequency domain characteristics of the clutter within each group's echo signal are similar to one another; furthermore, it should be noted that the accuracy of clutter feature analysis can be improved by performing channel estimation on multiple groups of echo signals followed by feature analysis. Also, the interval value The value depends on the distribution of clutter velocity (Doppler frequency shift) within the environment, and if the clutter velocity is faster or the proportion of high-speed clutter in the clutter velocity distribution within the environment is high, a narrower interval from the received echo signal of the first signal is used to ensure that the Doppler characteristics of the clutter are not lost in the echo signals of each group (i.e., to ensure that high-speed clutter can be reflected in the echo signals of each group). One, two, or more echo signals must be selected and divided into the same group, and accordingly, the number of echo signals within each group increases and the interval value ...is reduced. For example, with respect to the detection node, if the velocity distribution of clutter within the current detection scene is concentrated at zero (0) velocity, the interval value You can select a larger value for; and for the detection node, if the velocity distribution of clutter within the current detection scene is mainly high, the interval value You can choose a smaller value. The advantage of this is, By flexibly adjusting it, it is possible to ensure that multiple groups of echo signals can be obtained without loss of clutter rate information from each group of echo signals. After channel estimation based on multiple groups of echo signals, clutter feature extraction can effectively reduce the influence of noise and improve the accuracy of clutter feature extraction.

[0128] Optionally, the first channel estimation results of at least two groups One implementation method for obtaining is the echo signal of each group Performing DFT on to obtain the time-domain representation of the echo signal After obtaining the results, at least two groups of channel estimation results may be obtained by performing channel estimation using the LS (Least Squares) method.

[0129] Optionally, when grouping echo signals based on a preset interval value, the number of groups obtained by splitting is related to the number of echo signals obtained consecutively at that interval. In one example, each group of echo signals may contain different echo signals obtained at that interval, and the echo signals may be consecutive. In one example, the same echo signals may also be split into different groups of echo signals, for instance, when grouping, one group of echo signals has the same echo signal as another group of echo signals. For instance, assuming there are 10 echo signals and the interval value is 5, if one echo signal is obtained and grouped for every 5 intervals of echo signals, 5 groups of echo signals can be obtained by setting the number of groups to be equal to the interval value; if two or more echo signals are obtained and grouped for every 5 intervals of echo signals, and the number of groups is still equal to the interval value, the echo signals of different groups contain the same echo signal, that is, one echo signal is repeatedly sampled and split into different groups; When two or more echo signals are acquired and grouped at intervals of five echo signals, the number of groups set may be related to the number of two or more echo signals acquired in the interval, and in this case, they may be arranged to group the same echo signals without repeated sampling.

[0130] Optionally, before grouping the third channel estimation result or the echo signal, an operation to determine an interval value based on the Doppler frequency distribution of non-target objects within a preset detection scene may be performed.

[0131] The target objects within a preset detection scene include the objects to be detected within the detection scene. For example, assuming the current task is to detect unmanned aerial vehicles (UAVs) in the sky, the target objects within the detection scene at this point are the UAVs, and objects other than the UAVs are non-target objects (clutter), such as clouds, birds, etc., and interval values ​​can be determined based on a preset Doppler frequency distribution for the non-target objects. For example, assuming the current task is to detect ships in the sea, in this detection scenario, the ship is the target object, and objects other than the ship are non-target objects (clutter), such as seawater, fish, etc., and interval values ​​can be determined based on a preset Doppler frequency distribution for the non-target objects.

[0132] Optionally, the sensing node has at least two groups of first channel estimation results. A first clutter estimation result can be obtained by performing clutter feature analysis based on [the provided text]. The clutter feature analysis method may use Eigenvalue Decomposition (EVD) or Singular Value Decomposition (SVD). One possible embodiment is at least two groups of first channel estimation results. It is to perform SVD on, and here and, here and is an orthogonal matrix and is a diagonal matrix containing singular values. As a result of SVD, the first The matrix corresponding to (or Principal singular vector within ), Based on, A matrix for estimating the clutter subspace by selecting the maximum singular value within it It forms a matrix composed of these principal singular vectors. It can capture the key features of clutter echo. In this case, a matrix composed of principal singular vectors The complexity of clutter reconstruction based on this can be significantly reduced, and The value of can be 2 to 4 in typical outdoor scenes. It should be noted that the clutter feature analysis process can be real-time or non-real-time depending on the processing capability of the detection nodes. Real-time clutter feature analysis is, After receiving the echo signal, the detection node next It may be possible to extract clutter features by completing clutter feature analysis before acquiring echo signals; non-real-time clutter feature analysis is, After receiving the echo signal, the sensing node is the previous It may be possible to extract clutter features by completing clutter feature analysis based on the first echo of the dog; The value of depends on the data processing capability of the sensing node, and The larger the value, the lower the data processing capability of the detection node. The advantage of real-time clutter feature analysis by the detection node is that the extracted clutter features can reflect the current environmental clutter in real time and significantly improve detection performance after environmental clutter removal. If the detection node is capable of performing non-real-time clutter feature analysis, the extracted clutter features can be used for subsequent real-time clutter reconstruction and can perform clutter removal on the received echo signal.

[0133] Optionally, the first clutter estimation result obtained from clutter feature analysis includes a matrix for clutter reconstruction (the process of obtaining said matrix may be considered as the first clutter estimation). The detection node is a matrix composed of principal singular vectors. Based on this, a matrix for clutter reconstruction (a first clutter estimation result) can be obtained, and said matrix can be used for real-time clutter reconstruction and clutter removal. A possible embodiment for obtaining the clutter reconstruction matrix is ​​a matrix Based on It is to obtain, and the matrix It can be stored for later real-time clutter estimation. Alternatively, another implementation for obtaining a clutter reconstruction matrix is ​​a matrix Based on By obtaining, where the matrix and It can be stored for later real-time clutter estimation, which has the advantage of reducing the computational complexity of matrix multiplication. If the background environment changes, the matrix or and It should be noted that can no longer reflect clutter after the environmental change; therefore, to reflect the clutter after the environmental change, the clutter estimation method provided by the aforementioned embodiment is performed again to obtain a new matrix or and It is necessary to acquire.

[0134] Optionally, the detection node is the matrix used for clutter reconstruction (matrix or and ) and the first channel estimation results of at least two groups Based on this, the first clutter estimation result (sometimes referred to as the first clutter signal) can be reconstructed. One possible method for reconstructing the clutter estimation result is the reconstructed matrix and the first channel estimation results of at least two groups Based on, the reconstructed first clutter signal It includes the step of obtaining. Alternatively, one possible method for reconstructing a clutter signal is a matrix for reconstruction. and and the first channel estimation results of at least two groups Reconstructed clutter signal based on It includes the step of obtaining.

[0135] Optionally, if the detection node performs clutter removal on at least two groups of first channel estimation results, the at least two groups of first channel estimation results The reconstructed clutter signal is removed (first clutter removal), and the channel estimation result after the first clutter removal You can obtain. Specifically, the removal method is It may be. The detection node is the channel estimation result after the first clutter removal. Rearranging the internal elements, the channel estimation result after the first clutter removal (also referred to as the second channel estimation result) is obtained. One possible arrangement method is illustrated in FIG. 9, where The element of each group in the first column (each group element contains Ns sample points) is an index by Arranged in columns, The elements of each group in the second column (each group element contains Ns sample points) are the index by It is a method arranged in columns, The inner The element of each group in the column (each group element contains Ns sample points) is an index by Arranged in columns, finally the second channel estimation result forms.

[0136] Optionally, the first clutter estimate may be a non-real-time clutter estimate.

[0137] An embodiment of the present disclosure can process a cumulatively acquired group of echo signals, and when channel estimation is performed to obtain at least two groups of first channel estimation results, the computational complexity can be effectively reduced and processing efficiency improved by grouping the third channel estimation result or the echo signal based on a preset interval value; additionally, by performing clutter feature extraction based on a plurality of groups of channel estimation results, the influence of noise can be effectively reduced and the accuracy of clutter feature extraction can be increased, thereby effectively improving the detection capability of the detected target object.

[0138] In a possible embodiment, the provided method further comprises the step of performing at least one of the following operations 1 to 2 when it is determined to perform clutter estimation based on the second channel estimation result S104:

[0139] Operation 1: An operation of performing clutter estimation based on at least one of a first signal and a third channel estimation result to obtain a second clutter estimation result, and performing clutter removal on the third channel estimation result based on the second clutter estimation result to obtain a fourth channel estimation result, thereby performing target detection based on at least one of the second channel estimation result and the fourth channel estimation result.

[0140] The communication and sensing node may determine whether it is necessary to perform real-time clutter estimation (second clutter estimation) based on the second channel estimation result; for example, the second clutter estimation may be a real-time clutter estimation performed by the communication and sensing node based on at least one of the frequency domain signal of the received first signal and the third channel estimation result, and the acquired second clutter estimation result may be used to perform clutter removal.

[0141] Optionally, if the communication and sensing node determines that a second clutter estimation must be performed, the communication and sensing node performs the second clutter estimation based on the first signal and / or third channel estimation result to obtain the second clutter estimation result, and obtains the fourth channel estimation result by performing clutter removal on the third channel estimation result based on the second clutter estimation result. On the other hand, if the communication and sensing node determines that a second clutter estimation is not necessary, the communication and sensing node does not perform clutter estimation or clutter removal. Subsequently, depending on the decision result, the communication and sensing node may perform target detection based on the second channel estimation result and / or the fourth channel estimation result.

[0142] Operation 2: An operation of performing clutter estimation based on at least one of at least two groups of first channel estimation results obtained by splitting a first signal and an echo signal to obtain a third clutter estimation result, and performing clutter removal on at least two groups of first channel estimation results obtained by splitting the echo signal based on the third clutter estimation result to obtain a fifth channel estimation result, thereby performing target detection based on at least one of the second channel estimation result and the fifth channel estimation result.

[0143] The communication and sensing node may determine whether it is necessary to perform real-time clutter estimation (third clutter estimation) based on the second channel estimation result; for example, the third clutter estimation may be a real-time clutter estimation performed by the communication and sensing node based on at least one of at least two groups of first channel estimation results obtained by splitting the frequency domain signal and the echo signal of the received first signal, and the obtained third clutter estimation result may be used to perform clutter removal.

[0144] Optionally, if the communication and sensing node determines that it is necessary to perform a third clutter estimation, the communication and sensing node performs the third clutter estimation based on at least two groups of first channel estimation results obtained by splitting the first signal and / or echo signal to obtain a third clutter estimation result, and performs clutter removal on at least two groups of first channel estimation results obtained by splitting the echo signal based on the third clutter estimation result to obtain a fifth channel estimation result. On the other hand, if the communication and sensing node determines that a third clutter estimation is not necessary, the communication and sensing node does not perform clutter estimation and clutter removal. Subsequently, depending on the decision result, the communication and sensing node may perform target detection based on the second channel estimation result and / or the fifth channel estimation result.

[0145] In a possible embodiment, the operation of performing clutter estimation based on at least one of a first signal and a third channel estimation result to obtain a second clutter estimation result, and performing clutter removal on the third channel estimation result based on the second clutter estimation result, comprises the following:

[0146] An operation of constructing a first matrix of a clutter subspace based on at least one of the frequency domain signal of the first signal and the third channel estimation result;

[0147] The operation of obtaining a reconstructed second clutter estimation result by performing signal reconstruction based on the first matrix and the third channel estimation result; and

[0148] An operation to obtain the fourth channel estimation result by performing clutter removal on the third channel estimation result based on the second clutter estimation result.

[0149] Optionally, the sensing node acquires a projection matrix of the clutter subspace (sometimes referred to as the first matrix) (the process of acquiring the first matrix can be regarded as performing a second clutter estimation, which is a real-time clutter estimation). One possible way for the sensing node to acquire the clutter subspace is to construct the clutter subspace in the frequency domain using an LS algorithm based on the frequency domain signal (reference signal) of the transmitted sensing signal, and the sensing signal may be a symbol based on OFDM modulation. Specifically, the constructed clutter subspace is It can be expressed as, and here is my In the frequency domain signal of the detection signal, the It is a reference signal corresponding to the subcarrier, and is the number of detected signals, and is the number of subcarriers of the frequency domain signal of the detection signal. Based on the clutter subspace, the communication and detection nodes are the projection matrix of the clutter subspace. You can acquire, and also the number of subcarriers In this case, the communication and sensing nodes are Projection matrix of the clutter subspace It is possible to obtain a clutter subspace based on a third channel estimation result based on the same method, and to obtain a projection matrix based on the said clutter subspace. In a possible embodiment, one possible method for the sensing node of the present disclosure to obtain a clutter subspace may additionally be to construct a clutter subspace based on the frequency domain signal of the first signal and the third channel estimation result, and to obtain a first matrix based on the said clutter subspace.

[0150] Optionally, the detection node reconstructs a second clutter signal (sometimes referred to as the second clutter estimation result) based on the projection matrix of the clutter subspace. The reconstruction method may be such that the second clutter signal is obtained by multiplying the projection matrix of the clutter subspace by the third channel estimation result, which is obtained by the detection node performing channel estimation on the echo signal of the first signal. The third channel estimation result And, is the channel estimation result corresponding to a single sense signal; the sense signal may be a symbol modulated based on OFDM symbols, and is the frequency domain estimation result corresponding to a single subcarrier of the frequency domain detection signal. may be the third channel estimation result in the aforementioned embodiment, and an example of obtaining the channel estimation result will not be described herein. The sensing node is Projection matrix of the clutter subspace Second clutter signal based on Acquires, and here , is the frequency domain estimation result corresponding to a single subcarrier of the frequency domain detection signal.

[0151] Optionally, the sensing node is the third channel estimation result Second clutter signal reconstructed from By removing (second clutter removal), the fourth channel estimation result (Sometimes referred to as the channel estimation result after second clutter removal) is obtained. Specifically, the removal method It could be.

[0152] In a possible embodiment, the operation of obtaining a third clutter estimation result by performing clutter estimation based on at least one of at least two groups of first channel estimation results obtained by splitting the first signal and the echo signal, and obtaining a fifth channel estimation result by performing clutter removal on at least two groups of first channel estimation results obtained by splitting the echo signal based on the third clutter estimation result, comprises the following:

[0153] Constructing a second matrix of the clutter subspace based on at least one of at least two groups of first channel estimation results obtained by splitting the frequency domain signal and the echo signal of the first signal;

[0154] Performing signal reconstruction based on at least two groups of first channel estimation results obtained by splitting the second matrix and the echo signal, thereby obtaining a reconstructed third clutter estimation result; and

[0155] Obtaining a fifth channel estimation result by performing clutter removal on at least two groups of first channel estimation results obtained by splitting the echo signal based on the third clutter estimation result.

[0156] Optionally, the method of constructing the second matrix (projection matrix) of the clutter subspace and the method of obtaining the third clutter estimation result by performing signal reconstruction may be performed by referring to the method of obtaining the first matrix and the second clutter estimation result in the above-described embodiment, and will not be described in detail in the present disclosure.

[0157] Optionally, after obtaining the fourth channel estimation result or the fifth channel estimation result, the following step is additionally included:

[0158] A step of determining whether target detection based on the fourth channel estimation result or the fifth channel estimation result satisfies the first condition;

[0159] When the above first condition is satisfied, a step of constructing a third matrix of the clutter subspace based on the result of the target detection;

[0160] A step of obtaining a reconstructed fourth clutter estimation result by performing signal reconstruction based on the third matrix and third channel estimation result; or obtaining a fifth clutter estimation result by performing signal reconstruction based on at least two groups of first channel estimation results obtained by the division of the third matrix and echo signal; and

[0161] A step of obtaining a sixth channel estimation result by performing clutter removal on the third channel estimation result based on the fourth clutter estimation result; or obtaining a seventh channel estimation result by performing clutter removal on at least two groups of first channel estimation results obtained by splitting the echo signal based on the fifth clutter estimation result.

[0162] Optionally, the method of constructing the third matrix (projection matrix) of the clutter subspace may be performed by referring to the method of constructing the first matrix of the clutter subspace in the aforementioned embodiment, and this will not be described in detail in the present disclosure.

[0163] In one example, the sensing node is the fourth channel estimation result Alternatively, the parameters of a desired target object can be detected and estimated by applying a target detection algorithm to the fifth channel estimation result. Specifically, the detection node For [the data], an inverse discrete Fourier transform (IDFT) is performed on a column-by-column basis to obtain a signal in the delay domain, and a DFT is performed on a row-by-row basis to obtain a signal in the Doppler domain, and the distance or velocity (Doppler frequency) of a single or multiple target objects can be detected through fixed threshold detection; where the distance can be obtained by multiplying the delay time by the speed of light and dividing by 2, and the velocity can be obtained by multiplying the Doppler frequency by the wavelength of the detected signal and dividing by 2.

[0164] Optionally, the detection node may determine whether there exists a target object satisfying the first condition based on the target detection result or during the target detection process; if there exists, the aforementioned step of determining whether the first condition is satisfied is repeated, and if there does not exist, the process is terminated.

[0165] Optionally, the first condition includes at least one of the following:

[0166] (1) The power of the fourth channel estimation result or the fifth channel estimation result of the target object is detected to be greater than the power of the noise floor, and the detected Doppler frequency of the target object is not equal to 0;

[0167] Power of the fourth channel estimation result or the fifth channel estimation result of the target object this , and Doppler A decision is made regarding whether it satisfies; is the number of detected objects detected by the communication and sensing nodes, and (Unit: Watt) is a fixed threshold. Specifically, One possible value of is the power of the noise floor, and the power value of the noise floor can be a theoretical value or an actual measured value. The advantage of setting the condition in this way is that the power of the fourth-channel estimation result or the fifth-channel estimation result of an actual target object with a non-zero Doppler is When it is larger, a false target may be generated at the corresponding same distance, and the condition can reduce the impact on target detection due to clutter removal by rapidly screening out the actual target object where the false target may occur.

[0168] (2) The power of the fourth channel estimation result or the fifth channel estimation result of the target object is detected to be greater than the power of the noise floor (greater than 0), and the detected Doppler frequency of the target object is an integer multiple of the non-zero Doppler resolution.

[0169] Power of the fourth channel estimation result or the fifth channel estimation result of the target object this , and Doppler A decision is made regarding whether it satisfies; is the number of detected objects detected by the communication and sensing nodes, and (Unit: Watt) is a fixed threshold, and (Unit: Hertz) is the Doppler resolution. Specifically, One possible value of is the power of the noise floor, and the power of the noise floor can be a theoretical value or an actual measured value. The advantage of setting the condition in this way is that when the Doppler of a real target object with a non-zero Doppler is an integer multiple of the Doppler resolution, the power of the corresponding 4th channel estimation result or 5th channel estimation result of a sham object at the same distance will be higher, and the condition can effectively select the real target object with the higher power among the corresponding 4th channel estimation result or 5th channel estimation result of the sham object, thereby reducing the computational complexity of the clutter subspace projection matrix and reducing the impact on target detection due to clutter removal.

[0170] (3) The power of the fourth channel estimation result or the fifth channel estimation result of the target object corresponding to at least one of the preset distance and preset angle is detected to be greater than the power of the noise floor, and the detected Doppler frequency of the target object is not equal to 0.

[0171] In relation to condition (1) within the first condition, condition (3) additionally considers at least one of distance and angle. In some specific scenarios, it may be necessary to consider a situation within a specific distance or under a specific angle, and in this case, in order to effectively reduce computational complexity and increase target detection efficiency, consideration may be made based on the fourth channel estimation result or the fifth channel estimation result of a target object corresponding to at least one of the distance and angle preset for the requirements of the current detection operation.

[0172] (4) The power of the fourth channel estimation result or the fifth channel estimation result of the target object corresponding to at least one of the preset distance and preset angle is detected to be greater than the power of the noise floor, and the detected Doppler frequency of the target object is an integer multiple of the non-zero Doppler resolution.

[0173] In relation to condition (2) within the first condition, condition (4) additionally considers at least one of distance and angle. In some specific scenarios, it may be necessary to consider a situation within a specific distance or under a specific angle, and in this case, in order to effectively reduce computational complexity and improve the efficiency of target detection, consideration may be made based on the fourth channel estimation result or the fifth channel estimation result of a target object corresponding to at least one of the preset distance and preset angle for the requirements of the current detection operation.

[0174] It should be noted that if the power of the fourth channel estimation result or the fifth channel estimation result of a target object having a non-zero Doppler frequency is high, a false object may be generated due to clutter removal performed after real-time clutter estimation, which may increase the false alarm probability. Specifically, the Doppler frequency of the false object is zero, and it is located at the same distance as the detected target object having a non-zero Doppler frequency. The advantage of using the first condition to select a detected target object satisfying the condition is that the influence of the false object caused by the object can be suppressed by simply identifying the detected target object that causes the false object.

[0175] In one example, the detection node acquires a new clutter subspace projection matrix based on the target detection result and then performs clutter signal reconstruction. Specifically, the detection node clutter subspace A new clutter subspace based on It can constitute; is my The signal within the frequency domain of the detection signal It is a reference signal corresponding to the subcarrier, and is the number of detected signals, and is the number of subcarriers of the frequency domain signal of the detection signal, where And, is having non-zero Doppler in S905 It is the Doppler frequency corresponding to the number of detected target objects, and is the signal duration of the detection signal, and is the number of detected signals. Based on the new clutter subspace, the communication and detection nodes are the projection matrix of the new clutter subspace. You can acquire, and the number of subcarriers In this case, the communication and sensing nodes are of the new clutter subspace projection matrices It is possible to obtain [this]. It is worth noting that when constructing a clutter signal using a new clutter subspace projection, the advantage is that it can effectively suppress false objects generated at an equidistant zero-Doppler frequency by target objects with high Doppler frequencies and reduce the probability of false alarms.

[0176] In a possible embodiment, the operation of deciding to perform clutter estimation based on the second channel estimation result includes the following:

[0177] Determining whether the above second channel estimation result satisfies a preset second condition;

[0178] Deciding to perform clutter estimation if the second channel estimation result satisfies the second condition; and

[0179] If the second channel estimation result does not satisfy the second condition, performing target detection based on the second channel estimation result.

[0180] Optionally, the sensing node is the second channel estimation result Based on this, whether the second condition is satisfied is determined, and if the second condition is satisfied, real-time clutter estimation and clutter removal are performed, and if the second condition is not satisfied, target object detection can be performed based on the second channel estimation result.

[0181] Optionally, the sensing node is the second channel estimation result By applying a target detection algorithm to it, the parameters of the desired target object can be detected and estimated. Specifically, the detection node For the IDFT, a signal in the delay domain is obtained by performing the IDFT on a column-by-column basis, and a signal in the Doppler domain is obtained by performing the DFT on a row-by-row basis, and the distance or velocity (Doppler frequency) of a single or multiple target objects can be detected through fixed threshold detection; where the distance can be obtained by multiplying the delay time by the speed of light and dividing by 2, and the velocity can be obtained by multiplying the Doppler frequency by the wavelength of the detected signal and dividing by 2.

[0182] Optionally, the second condition includes at least one of the following:

[0183] (1) The power of the noise floor of the second channel estimation result is greater than or equal to a preset threshold related to the distance of the detected target object and / or the RCS of the target object.

[0184] 2nd channel estimation result The power of the noise floor (unit: watts) is Larger than; The value of (unit: watts) may be the power of the noise floor of the channel estimation result after performing first clutter estimation and removal based on the channel estimation result, and (Unit: Watt) is a positive number greater than 0, and its value varies depending on the target object recognized within the environment. Specifically, It can have a larger value if the target object is close or / or has a higher RCS; It can have a value of 0 or less if the target object is far away or / or the RCS is small. The power of the noise floor If it is larger, this may indicate that the clutter estimation results reconstructed based on the clutter reconstruction matrix cannot reflect the clutter of the current environment, and as a result, residual clutter components will remain even after clutter removal by the detection node, affecting the detection of actual target objects.

[0185] (2) The power of the channel estimation result corresponding to the zero Doppler frequency in the second channel estimation result is greater than or equal to a preset threshold.

[0186] The zero Doppler frequency represents the Doppler frequency at which the target object is stationary, that is, at which the velocity is zero.

[0187] (2.1) The average power of the channel estimation result corresponding to the zero Doppler component in the second channel estimation result is greater than or equal to a preset threshold related to the distance of the detected target object and / or the RCS of the target object.

[0188] Channel estimation result corresponding to the zero Doppler component after clutter removal The average power (unit: watts) is Larger than, and here The value of (unit: watts) may be the average power of the estimation result of the zero Doppler component after clutter estimation and removal based on the channel estimation result, and (Unit: Watt) is a positive number greater than 0, and its value varies depending on the target object recognized within the environment. Specifically, It can have a larger value if the target object is close or / or has a higher RCS; It can have a value of 0 or less if the target object is far away or / or the RCS is small. The average power of If it is greater than this, it may indicate that the clutter estimation results reconstructed based on the clutter reconstruction matrix cannot reflect the zero-Doppler clutter component (static) of the current environment, and as a result, residual zero-Doppler clutter components will remain even after clutter removal by the detection node, affecting the detection of static actual target objects.

[0189] (2.2) The maximum power of the channel estimation result corresponding to the zero Doppler component in the second channel estimation result is greater than or equal to a preset threshold related to the distance of the detected target object and / or the RCS of the target object.

[0190] Channel estimation result corresponding to the zero Doppler component after clutter removal The maximum power of is Larger than, and here (Unit: Watt) may be the maximum power of the zero-Doppler component estimation result after clutter estimation and removal based on the channel estimation result, and (Unit: Watt) is a positive number greater than 0, and its value varies depending on the target object recognized within the environment. Specifically, It can have a larger value if the target object is close or / or has a higher RCS; It can have a value of 0 or less if the target object is far away or / or the RCS is small. The maximum power of By determining whether it is greater, it is possible to easily and quickly determine whether the clutter estimation result reconstructed based on the clutter reconstruction matrix can also reflect the zero-Doppler clutter component of the current environment (static state), and as a result, residual zero-Doppler clutter component will remain even after clutter removal by the detection node, affecting the detection of static actual target objects.

[0191] (3) The power of the noise floor corresponding to at least one of the preset distance and preset angle in the second channel estimation result is greater than or equal to a preset threshold.

[0192] In relation to condition (1) of the second condition, condition (3) may include consideration of at least one of distance and angle, and in some detection scenarios, specific conditions under specific distance and angle may be considered, and in order to effectively reduce computational complexity and increase target detection efficiency, a low-noise function corresponding to at least one of the preset distance and preset angle among the second channel estimation results may be considered for the current detection requirements.

[0193] (4) The power of the channel estimation result corresponding to the zero Doppler frequency corresponding to at least one of the preset distance and preset angle in the second channel estimation result is greater than or equal to a preset threshold.

[0194] In relation to condition (2) of the second condition, condition (4) is additionally considered to include at least one of distance and angle. In some specific scenarios, it may be necessary to consider the situation within a specific distance or under a specific angle, and in this case, in order to effectively reduce computational complexity and improve the efficiency of target detection, the channel estimation result corresponding to the zero Doppler frequency according to at least one of a preset distance and a preset angle in relation to the requirements of the current detection operation may be considered.

[0195] The method provided by the present disclosure is described below in relation to several optional embodiments (the order of the first, second, third, etc. in the following embodiments is independent of the expressions in the above embodiments, that is, the expressions of the order of the first, second, etc. in the following embodiments 1 to 5 are functionally valid only within the respective embodiments).

[0196] Example 1

[0197] This embodiment provides an adaptive clutter estimation and removal method, which is shown in FIG. 5, and the specific steps are as follows.

[0198] According to an embodiment of the present disclosure, in step S401, the communication and sensing node performs a first clutter estimation, and then, based on the result of the first clutter estimation, performs a first clutter removal on the echo signal of the transmitted first signal. The first clutter estimation may be the aforementioned non-real-time clutter estimation, and the result of the clutter estimation cannot be obtained in real time, but can only be obtained after a required specific processing time (as in Example 2), and it is impossible to perform clutter removal on the currently received echo signal based on the result of the first clutter estimation. After obtaining the result of the first clutter estimation, the communication and sensing node may perform real-time clutter reconstruction based on the result of the first clutter estimation, and may perform a first clutter removal on the echo signal of the transmitted first signal (e.g., the channel estimation result after the first clutter removal) (as in Example 3); wherein the first signal may be a signal transmitted by the communication and sensing node for detection.

[0199] According to an embodiment of the present disclosure, in step S402, the communication and sensing node determines whether it is necessary to perform a second clutter estimation based on the echo signal after the first clutter removal (as in Example 5); specifically, the second clutter estimation may be a real-time clutter estimation that can be performed based on the echo signal received by the communication and sensing node, and the acquired second clutter estimation result may be used to perform clutter removal on the currently received echo signal (e.g., a channel estimation result corresponding to the echo signal) (as in Example 4). If the communication and sensing node determines that the second clutter estimation must be performed, the communication and sensing node performs the second clutter estimation to obtain the second clutter estimation result and performs the second clutter removal on the echo signal based on the second clutter estimation result. On the other hand, if the communication and sensing node determines that the second clutter estimation is not necessary, the communication and sensing node does not perform the second clutter estimation and the second clutter removal.

[0200] According to an embodiment of the present disclosure, in step S403, the communication and sensing node performs target object detection based on the echo signal after the first and / or second clutter removal.

[0201] Example 2

[0202] FIG. 6 illustrates a flowchart of a method for estimating a first clutter according to an embodiment of the present disclosure.

[0203] According to Example 1, a method for a communication and sensing node to perform a first clutter estimation is shown in FIG. 6:

[0204] According to an embodiment of the present disclosure, in step S501, the sensing node transmits a sensing signal and an echo signal Receives, where a positive integer is the number of echoes received by the sensing node, and is a positive integer is the number of sampling points of a single echo.

[0205] According to an embodiment of the present disclosure, in step S502, the sensing node performs channel estimation for the echo signal and the channel estimation result It obtains. Specifically, an embodiment of obtaining a channel estimation result is an echo signal Time-domain representation of the echo signal by performing DFT on it By obtaining and then performing channel estimation using the LS (Least Square) method It is to acquire; is a reference signal.

[0206] According to an embodiment of the present disclosure, in step S503, the sensing node obtains a channel estimation result By grouping Acquire channel estimation results for groups; the number of channel estimation results within each group is and the number of frequency domain sampling points within each group is is. That is, For the channel estimation results, each Select one channel estimation result for each channel estimation result, group them into the same group, and the channel estimation results If you group them, the grouped channel estimation results ...can be obtained. Specifically, one possible grouping method is illustrated in FIG. 7, and when the index of the channel estimation result for the received echo signal is {1, 2, ..., Np}, the set of indices of the echo signal constituting the channel estimation result of the first group is And, the set of indexes of echo signals constituting the channel estimation result of the second group is and, in this way, my The set of indexes of echo signals constituting the group's channel estimation results is am. The value of is a positive integer greater than 1, and It is a divisor of. It should be noted that the advantage of grouping channel estimation results is that, through the grouping mentioned above, all major frequency domain characteristics of the clutter, such as the Doppler frequency shift characteristics of the clutter included in the channel estimation results of each group, can be preserved, and the frequency domain characteristics of the clutter within the channel estimation results of each group are similar to one another; furthermore, it should be noted that the accuracy of clutter feature analysis can be improved by performing feature analysis on the channel estimation results of multiple groups. In addition, the number of groups The value depends on the distribution of clutter velocity (Doppler frequency shift) within the environment, and if the clutter velocity is faster or the proportion of high-speed clutter in the distribution of clutter velocity within the environment is high, in order to ensure that the Doppler characteristics of the clutter are not lost in the channel estimation results of each group (i.e., to ensure that high-speed clutter can be reflected in the channel estimation results of each group), the channel estimation results for the received echo signal A narrower gap from You must select a single channel estimation result and split it into the same group; accordingly, the number of channel estimation results within each group increases, and the number of groups ...will decrease. For example, regarding a detection node, if the velocity distribution of clutter within the current detection scene is mainly zero velocity, the number of groups You can select a larger value for; and for the detection node, if the velocity distribution of clutter within the current detection scene is mainly high, the number of groups You can choose a smaller value. The advantage of this is, By flexibly adjusting it, it is possible to ensure that channel estimation results of multiple groups are obtained without loss of clutter velocity information in the channel estimation results of each group, and furthermore, clutter feature extraction based on channel estimation results of multiple groups can effectively reduce the influence of noise and improve the accuracy of clutter feature extraction.

[0207] According to an embodiment of the present disclosure, in step S504, the sensing node is a grouped channel estimation result Clutter feature analysis is performed based on, and the method for performing clutter feature analysis may be to use EVD or SVD. Specifically, one possible implementation is grouped channel estimation results. It is to perform SVD on, and here and, here and is an orthogonal matrix and is a diagonal matrix containing singular values. As a result of SVD, the first The matrix corresponding to (or Principal singular vector within ), Based on, A matrix for estimating the clutter subspace by selecting the maximum singular value within it It forms a matrix composed of these principal singular vectors. It can capture the key features of clutter echo. In this case, a matrix composed of principal singular vectors The complexity of clutter reconstruction based on this can be significantly reduced, and The value of can be 2 to 4 in typical outdoor scenes. It should be noted that the clutter feature analysis process can be real-time or non-real-time depending on the processing capability of the detection node. Real-time clutter feature analysis is, the detection node After receiving the echo signal, the detection node next It may be possible to extract clutter features by completing clutter feature analysis before acquiring echo signals; non-real-time clutter feature analysis, wherein the detection node is After receiving the echo signal, the sensing node is the previous It may be possible to extract clutter features by completing clutter feature analysis based on the first echo of the dog; The value of depends on the data processing capability of the sensing node, and The larger the value, the lower the data processing capability of the detection node. The advantage of real-time clutter feature analysis by the detection node is that the extracted clutter features can reflect the current environmental clutter in real time and significantly improve detection performance after environmental clutter removal. If the detection node can perform only non-real-time clutter feature analysis, the extracted clutter features can be used for subsequent real-time clutter reconstruction and can perform clutter removal on the received echo signal.

[0208] According to an embodiment of the present disclosure, in step S505, the sensing node is a matrix composed of major singular vectors. Based on this, a matrix for clutter reconstruction (first clutter estimation) is obtained, which can be used for real-time clutter reconstruction and clutter removal. A possible embodiment for obtaining the clutter reconstruction matrix is ​​a matrix Based on It is to obtain, and the matrix It can be stored for later real-time clutter estimation. Alternatively, another implementation for obtaining a clutter reconstruction matrix is ​​a matrix Based on By obtaining, where the matrix and It can be stored for later real-time clutter estimation, which has the advantage of reducing the computational complexity of matrix multiplication. The specific process of performing clutter reconstruction based on the clutter reconstruction matrix is ​​described in detail in Example 3. It should be noted that when the background environment changes, the matrix , or and A may no longer reflect clutter after an environmental change, and therefore, to reflect clutter after an environmental change, a new matrix according to steps S501 to S505 , or and The point is that it must be reacquired.

[0209] Example 3

[0210] According to Example 1, a method for a communication and sensing node to perform a first clutter removal is shown in FIG. 8:

[0211] S701: The detection node transmits a detection signal and an echo signal Receives, where a positive integer is the number of echoes received by the sensing node, and is a positive integer is the number of sampling points of a single echo.

[0212] S702: The sensing node performs channel estimation on the echo signal and the channel estimation result It obtains. Specifically, an embodiment of obtaining a channel estimation result is an echo signal Time-domain representation of the echo signal by performing DFT on it Acquire, and then perform channel estimation using the LS method. It is to acquire; is a reference signal.

[0213] S703: The detection node is the channel estimation result By grouping Obtaining channel estimation results for groups; the number of echoes within each group is and the number of frequency domain sampling points within each group is is. Subsequently, the grouped channel estimation results is the channel estimation result It can be obtained after grouping; specifically, one possible grouping method is illustrated in FIG. 7, and when the index of the channel estimation result for the received echo signal is {1, 2, ..., Np}, the set of indices of the echo signal constituting the channel estimation result of the first group is And, the set of indexes of echo signals constituting the channel estimation result of the second group is and, in this way, my The set of indexes of echo signals constituting the group's channel estimation results is am.

[0214] S704: Detection node matrix for clutter reconstruction and grouped channel estimation results Reconstructs the clutter signal based on. Matrix for clutter reconstruction or and The acquisition of can be verified in Example 2 and will not be described in detail here. One possible method for reconstructing the clutter signal is a reconstructed matrix and grouped channel estimation results Clutter signal reconstructed based on It is to obtain. Alternatively, one possible method for reconstructing the clutter signal is the reconstructed matrix and and grouped channel estimation results Clutter signal reconstructed based on It is to acquire.

[0215] S705: The detection node is the grouped channel estimation result The reconstructed clutter signal is removed (first clutter removal), and the channel estimation result after clutter removal Acquires. Specifically, the removal method is It could be.

[0216] S706: Detection node channel result after clutter removal By rearranging the elements in Obtains. One possible arrangement method is illustrated in FIG. 9, and The element of each group in the first column (each group element contains Ns sample points) is an index by Arranged in columns, The elements of each group in the second column (each group element contains Ns sample points) are the index by It is a method arranged in columns, The inner The element of each group in the column (each group element contains Ns sample points) is an index by Arranged in columns, finally the channel estimation result after clutter removal Constitutes.

[0217] S707: The detection node is the channel estimation result By applying a target detection algorithm to it, the parameters of the desired target object can be detected and estimated. Specifically, the detection node For the IDFT, a signal in the delay domain is obtained by performing the IDFT on a column-by-column basis, and a signal in the Doppler domain is obtained by performing the DFT on a row-by-row basis, and the distance or velocity (Doppler frequency) of a single or multiple target objects can be detected through fixed threshold detection; where the distance can be obtained by multiplying the delay time by the speed of light and dividing by 2, and the velocity can be obtained by multiplying the Doppler frequency by the wavelength of the detected signal and dividing by 2.

[0218] Example 4

[0219] According to Example 1, a method for a communication and sensing node to perform second clutter estimation and second clutter removal is shown in FIG. 10:

[0220] S901: The sensing node obtains the projection matrix of the clutter subspace (second clutter estimation). One possible way for the sensing node to obtain the clutter subspace is to construct the clutter subspace in the frequency domain using an LS algorithm based on the frequency domain signal (reference signal) of the transmitted sensing signal, and the sensing signal may be a symbol based on OFDM modulation. Specifically, the constructed clutter subspace is It can be expressed as, and here is my In the frequency domain signal of the detection signal, the It is a reference signal corresponding to the subcarrier, and is the number of detected signals, and is the number of subcarriers of the frequency domain signal of the detection signal. Based on the clutter subspace, the communication and detection nodes are the projection matrix of the clutter subspace. You can acquire, and also the number of subcarriers In this case, the communication and sensing nodes are Projection matrix of the clutter subspace You can obtain.

[0221] S902: The detection node reconstructs the clutter signal based on the projection matrix of the clutter subspace. The reconstruction method may be for the detection node to acquire the clutter signal by multiplying the channel estimation result by the projection matrix of the clutter subspace. The channel estimation result is and, here is the channel estimation result corresponding to a single sense signal; the sense signal may be a symbol modulated based on OFDM symbols, and is the frequency domain estimation result corresponding to a single subcarrier of the frequency domain detection signal. It can be obtained in the manner of S701 and S702 of Example 3, and will not be described in detail herein. The detection node is of the clutter subspace. projection matrices Clutter signal based on Acquires, and here and, here is the frequency domain estimation result corresponding to a single subcarrier of the frequency domain detection signal.

[0222] S903: The detection node is the channel estimation result Clutter signal reconstructed from By removing (second clutter removal), the channel estimation result after clutter removal Acquires. Specifically, the removal method is It could be.

[0223] S904: The detection node is the channel estimation result By applying a target detection algorithm to it, the parameters of the desired target object can be detected and estimated. Specifically, the detection node For the IDFT, a signal in the delay domain is obtained by performing the IDFT on a column-by-column basis, and a signal in the Doppler domain is obtained by performing the DFT on a row-by-row basis, and the distance or velocity (Doppler frequency) of a single or multiple target objects can be detected through fixed threshold detection; where the distance can be obtained by multiplying the delay time by the speed of light and dividing by 2, and the velocity can be obtained by multiplying the Doppler frequency by the wavelength of the detected signal and dividing by 2.

[0224] S905: Based on the target detection result of S904, the detection node determines whether the target object satisfies the first condition; if satisfied, proceed to S906, otherwise the process is terminated.

[0225] Specifically, the first condition may be at least one of the following:

[0226] (1) Power of the channel estimation result after the second clutter removal for the target object this , and Doppler The decision being made regarding whether it satisfies, where is the number of detection targets detected by the communication and detection nodes, and (Unit: Watt) is a fixed threshold, and specifically, One possible value of is the power of the noise floor, and the power value of the noise floor can be a theoretical value or an actual measured value. The advantage of setting the condition in this way is that the power of the channel estimation result after the second clutter removal of an actual target object with a non-zero Doppler is When it is larger, false objects may be generated at the corresponding same distance, and the condition can reduce the impact on object detection due to clutter removal by rapidly screening out actual object objects where false objects may occur.

[0227] (2) Power of the channel estimation result after removing the second clutter of the target object this , and Doppler The decision being made regarding whether it satisfies, where is the number of detected objects detected by the communication and sensing nodes, and (Unit: Watt) is a fixed threshold, and (Unit: Hertz) is the Doppler resolution. Specifically, One possible value of is the power of the noise floor, and the power of the noise floor can be a theoretical value or an actual measured value. The advantage of setting the condition in this way is that when the Doppler of a real target object with a non-zero Doppler is an integer multiple of the Doppler resolution, the power of the channel estimation result after second channel clutter removal of a spurious object at the corresponding same distance will be higher, and this condition effectively selects real target objects with higher power channel estimation results after second clutter removal of spurious objects, thereby reducing the computational complexity of the clutter subspace projection matrix and reducing the impact on target detection caused by clutter removal.

[0228] (3) The power of the channel estimation result after the second clutter removal of the target object corresponding to at least one of the preset distance and preset angle is detected to be greater than the power of the noise floor, and the detected Doppler frequency of the target object is not equal to 0.

[0229] (4) The power of the channel estimation result after the second clutter removal of the target object corresponding to at least one of the preset distance and preset angle is detected to be greater than the power of the noise floor, and the detected Doppler frequency of the target object is an integer multiple of the non-zero Doppler resolution.

[0230] It should be noted that if the power of the channel estimation result after the second clutter removal of a target object having a non-zero Doppler frequency is high, a false object will be generated due to the clutter removal of S903, and this will increase the probability of a false alarm. Specifically, the Doppler frequency of the false object is zero, and it is located at the same distance as the detected target object having a non-zero Doppler frequency. The advantage of using the first condition to select a detected target object satisfying the condition is that the effect caused by the false object can be suppressed by simply filtering out the detected target object that causes the false object.

[0231] S906: The detection node obtains a new clutter subspace projection matrix based on the target detection result, and then performs S902. Specifically, the detection node clutter subspace A new clutter subspace based on It can constitute; is my The signal within the frequency domain of the detection signal It is a reference signal corresponding to the subcarrier, and is the number of detected signals, and is the number of subcarriers of the frequency domain signal of the detection signal, where And, is having non-zero Doppler in S905 It is the Doppler frequency corresponding to the number of detected target objects, and is the signal duration of the detection signal, and is the number of detected signals. Based on the new clutter subspace, the communication and detection nodes are the projection matrix of the new clutter subspace. You can acquire, and the number of subcarriers In this case, the communication and sensing nodes are of the new clutter subspace projection matrices It is possible to obtain [this]. It is worth noting that when constructing a clutter signal using a new clutter subspace projection, the advantage is that it can effectively suppress false objects generated at an equidistant zero-Doppler frequency by target objects with high Doppler frequencies and reduce the probability of false alarms.

[0232] Example 5

[0233] According to Example 1, a method for determining whether a communication and sensing node performs a second clutter estimation and a second clutter removal based on an echo signal after the first clutter removal is shown in FIG. 11:

[0234] S1001: The sensing node performs channel estimation on the echo signal and the channel estimation result It obtains... Specifically, the implementation method for obtaining channel estimation results is the echo signal Time-domain representation of the echo signal by performing DFT on it Acquire, and then perform channel estimation using the LS method. It is to obtain, where a positive integer n is the number of echoes received by the sensing node, and is a positive integer is the number of sampling points of a single echo, and is a reference signal.

[0235] S1002: The detection node performs a first clutter removal on the channel estimation result, and the channel estimation result after the first clutter removal ...is obtained. It should be noted that the reconstruction matrix used to reconstruct the first clutter during the first clutter removal can be obtained based on the grouping described in Example 2 (specifically described in S504, which will not be described in detail here); additionally, in a conventional manner without grouping It is also possible to obtain a clutter reconstruction matrix by performing clutter feature extraction on echo signals based on echoes received from multiple groups of detection signals.

[0236] S1003: The detection node is the channel estimation result after the first clutter removal Based on this, the satisfaction of the second condition is determined, and if the second condition is satisfied, S1004 is performed, and if the second condition is not satisfied, S1005 is performed.

[0237] Specifically, the second condition may be at least one of the following:

[0238] (1) Channel estimation result after first clutter removal The power of the noise floor (unit: watts) is Larger than; The value of (unit: watts) may be the power of the noise floor of the channel estimation result after performing first clutter estimation and removal based on the channel estimation result, and (Unit: Watt) is a positive number greater than zero, and its value varies depending on the target object recognized within the environment. Specifically, It can have a larger value if the target object is close or / or has a higher RCS; It can have a value of 0 or less if the target object is far away or / or the RCS is small. The power of the noise floor If it is greater than this, it may indicate that the first clutter estimation result reconstructed based on the first clutter reconstruction matrix can no longer reflect the clutter of the current environment, and as a result, residual clutter components will remain even after the first clutter removal by the detection node, affecting the detection of the actual target object.

[0239] (2) Channel estimation result corresponding to the zero Doppler component after first clutter removal The average power (unit: watts) is Larger than, and here The value of (unit: watts) may be the average power of the zero-Doppler component estimation result after clutter estimation and removal based on the channel estimation result, and (Unit: Watt) is a positive number greater than 0, and its value varies depending on the target object recognized within the environment. Specifically, It can have a larger value if the target object is close or / or has a higher RCS; It can have a value of 0 or less if the target object is far away or / or the RCS is small. The average power of If it is greater than this, it may indicate that the first clutter estimation result reconstructed based on the first clutter reconstruction matrix cannot reflect the zero-Doppler clutter component (static state) of the current environment, and as a result, residual zero-Doppler clutter component will remain even after the first clutter removal of the detection node, affecting the detection of static actual target objects.

[0240] (3) Channel estimation result corresponding to the zero Doppler component after first clutter removal The maximum power of is Larger than, and here (Unit: Watt) may be the maximum power of the first clutter estimation and zero Doppler component estimation result after removal based on the channel estimation result, and (Unit: Watt) is a positive number greater than 0, and its value varies depending on the target object recognized within the environment. Specifically, It can have a larger value if the target object is close or / or has a higher RCS; It can have a value of 0 or less if the target object is far away or / or the RCS is small. The maximum power of By determining whether it is greater, it is possible to easily and quickly determine whether the first clutter estimation result reconstructed based on the first clutter reconstruction matrix can also reflect the zero Doppler clutter component (static state) of the current environment, and as a result, even after the first clutter removal by the detection node, a residual zero Doppler clutter component will remain and affect the detection of static actual target objects.

[0241] (4) The power of the noise floor corresponding to at least one of the preset distance and preset angle in the channel estimation result after the first clutter removal is greater than or equal to a preset threshold.

[0242] (5) The power of the channel estimation result corresponding to the zero Doppler frequency, which corresponds to at least one of the preset distance and preset angle in the channel estimation result after the first clutter removal, is greater than or equal to a preset threshold.

[0243] S1004: The detection node performs second clutter estimation and second clutter removal on the channel estimation result, and the channel estimation result after second clutter removal A method for obtaining a second clutter estimate and a second clutter removal is obtained. Specifically, the specific method for the second clutter estimate and second clutter removal may be the method described in Example 4; additionally, it may be a traditional clutter estimate and removal method that does not include S905 and S906.

[0244] S1005: The detection node is the channel estimation result By applying a target detection algorithm to it, the parameters of the desired target object can be detected and estimated. Specifically, the detection node For the IDFT, a signal in the delay domain is obtained by performing the IDFT on a column-by-column basis, and a signal in the Doppler domain is obtained by performing the DFT on a row-by-row basis, and the distance or velocity (Doppler frequency) of a single or multiple target objects can be detected through fixed threshold detection; where the distance can be obtained by multiplying the delay time by the speed of light and dividing by 2, and the velocity can be obtained by multiplying the Doppler frequency by the wavelength of the detected signal and dividing by 2.

[0245] It should be noted that the optional solutions provided in the various embodiments of the present disclosure described above may be implemented individually, or the steps of each embodiment or each embodiment may be implemented in combination with one another, provided that the implementation steps of different embodiments do not conflict.

[0246] Embodiments of the present disclosure also provide a node that may include a transceiver and at least one processor connected to said transceiver, said node may perform solutions provided by any alternative embodiments of the present disclosure based on the same principles as the methods provided by the embodiments of the present disclosure. said node may be an electronic device such as a UE or a network node.

[0247] Optionally, the node may be a first node, and at least one processor may be configured to perform any one of the methods performed by the first node provided by the embodiments of the present disclosure.

[0248] Embodiments of the present disclosure also provide an electronic device, the electronic device comprising at least one transceiver and at least one processor connected to at least one transceiver, and at least one processor is configured to perform methods provided in any optional embodiment of the present disclosure.

[0249] FIG. 12 illustrates a schematic structural diagram of an electronic device to which the solution of an embodiment of the present disclosure is applied. As illustrated in FIG. 12, the electronic device (4000) illustrated in FIG. 12 may include a processor (4001) and a memory (4003). The processor (4001) is connected to the memory (4003), for example, via a bus (4002). Optionally, the electronic device (4000) may further include a transceiver (4004), and the transceiver (4004) may be used for data interaction between the electronic device and another electronic device, for example, for transmitting data and / or receiving data. It should be noted that in actual applications, the number of transceivers (4004) is not limited to one, and the structure of the electronic device (4000) does not limit the embodiments of the present disclosure in any way. Optionally, the electronic device may be a node within a wireless communication system, for example, a first node. A node within the network may be a user terminal, or it may also be a base station or another network node.

[0250] The processor (4001) may be a central processing unit (CPU), a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It may implement or execute various exemplary logic blocks, modules, and circuits described in connection with the present disclosure. The processor (4001) may also be a combination for implementing computing functions, for example, a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0251] The bus (4002) may include a path for transmitting information between the aforementioned components. The bus (4002) may be a PCI (peripheral component interconnect) bus or an EISA (extended industry standard architecture) bus, etc. The bus (4002) may be an address bus, a data bus, a control bus, etc. For ease of representation, the bus is represented by only one bold line in FIG. 12. However, this does not mean that only one bus exists or that only one type of bus exists.

[0252] The memory (4003) may be, but is not limited to, a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, a random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, an optical disc storage (including compressed discs, laser discs, discs, digital multi-purpose discs, Blu-ray discs, etc.), a magnetic storage medium or other magnetic storage device, or any other medium capable of carrying or storing a desired program and accessible by a computer.

[0253] Memory (4003) is used to store an application program for executing an embodiment of the present disclosure and is controlled by a processor (4001). The processor (4001) is used to execute the application program stored in memory (4003) to implement the steps of the above-described method embodiment.

[0254] FIG. 13 is a block diagram of the internal structure of a UE according to one embodiment. Also, the UE of FIG. 13 corresponds to the UE of FIG. 3.

[0255] As illustrated in FIG. 13, a UE according to one embodiment may include a transceiver (1310), a memory (1320), and a processor (1330). The transceiver (1310), memory (1320), and processor (1330) of the UE may operate according to the communication method of the UE described above. However, the components of the UE are not limited thereto. For example, the UE may include more or fewer components than described above. Additionally, the processor (1330), transceiver (1310), and memory (1320) may be implemented as a single chip. Additionally, the processor (1330) may include at least one processor.

[0256] The transceiver (1310) collectively refers to a UE receiver and a UE transmitter and can transmit / receive signals to / from a base station or network entity. The signals transmitted / received to / from a base station or network entity may include control information and data. The transceiver (1310) may include an RF transmitter that up-converts and amplifies the frequency of the transmitted signal, and an RF receiver that low-noise amplifies and down-converts the frequency of the received signal. However, this is merely an example of the transceiver (1310), and the components of the transceiver (1310) are not limited to an RF transmitter and an RF receiver.

[0257] Additionally, the transceiver (1310) can receive a signal through a wireless channel and output it to a processor (1330), and can transmit the signal output from the processor (1330) through a wireless channel.

[0258] The memory (1320) can store programs and data necessary for the operation of the UE. Additionally, the memory (1320) can store control information or data included in signals acquired by the UE. The memory (1320) may be a storage medium such as read-only memory (ROM), random access memory (RAM), a hard disk, a CD-ROM, and a DVD, or a combination of these storage media.

[0259] The processor (1330) can control a series of processes to enable the UE to operate as described above. For example, the transceiver (1310) can receive a data signal including a control signal transmitted by a base station or network entity, and the processor (1330) can determine the result of receiving the control signal and data signal transmitted by the base station or network entity.

[0260] FIG. 14 is a block diagram of the internal structure of a base station or network entity according to one embodiment. Additionally, the base station or network entity of FIG. 14 corresponds to BS of FIG. 2.

[0261] As illustrated in FIG. 14, a base station or network entity according to one embodiment may include a transceiver (1410), a memory (1420), and a processor (1430). The transceiver (1410), memory (1420), and processor (1430) of the base station or network entity may operate according to the communication method of the base station or network entity described above. However, the components of the base station or network entity are not limited thereto. For example, the base station or network entity may include more or fewer components than described above. Additionally, the processor (1430), transceiver (1410), and memory (1420) may be implemented as a single chip. Additionally, the processor (1430) may include at least one processor.

[0262] The transceiver (1410) collectively refers to a base station (or network entity) receiver and a base station (or network entity) transmitter, and can transmit / receive signals to / from a terminal, network entity, or base station. The signals transmitted / received to / from a terminal, network entity, or base station may include control information and data. The transceiver (1410) may include an RF transmitter that up-converts and amplifies the frequency of a transmitted signal, and an RF receiver that low-noise amplifies and down-converts the frequency of a received signal. However, this is merely an example of a transceiver (1410), and the components of the transceiver (1410) are not limited to an RF transmitter and an RF receiver.

[0263] Additionally, the transceiver (1410) can receive a signal through a wireless channel and output it to a processor (1430), and can transmit the signal output from the processor (1430) through a wireless channel.

[0264] The memory (1420) can store programs and data necessary for the operation of a base station or network entity. Additionally, the memory (1420) can store control information or data included in a signal acquired by the base station or network entity. The memory (1420) may be a storage medium such as read-only memory (ROM), random access memory (RAM), a hard disk, a CD-ROM, and a DVD, or a combination of these storage media.

[0265] The processor (1430) can control a series of processes to cause the base station or network entity to operate as described above. For example, the transceiver (1410) can receive a data signal including a control signal transmitted by the terminal or network entity or base station, and the processor (1430) can determine the result of receiving the control signal and data signal transmitted by the terminal or network entity or base station.

[0266] An embodiment of the present disclosure provides a computer-readable storage medium in which a computer program is stored, and the computer program implements the steps and contents of the above-described method embodiment when executed by a processor.

[0267] Embodiments of the present disclosure also provide a computer program product including a computer program, and the computer program implements the steps and contents of the above-described method embodiment when executed by a processor.

[0268] Terms such as “first,” “second,” “third,” “fourth,” “1,” and “2 (if present)” as used in the detailed description, claims, and drawings of this disclosure are used to distinguish similar objects and are not necessarily used to define a specific order or sequence. It should be understood that data used in this manner may be used interchangeably where appropriate, and accordingly, embodiments of this disclosure described herein may be implemented in an order different from the order exemplified or described herein.

[0269] It should be understood that although the steps in the flowchart of the embodiments of the present disclosure are indicated sequentially by arrows, the steps are not necessarily performed in the order indicated by the arrows. Additionally, based on actual implementation scenarios, some or all of the steps in the flowchart may include multiple sub-steps or multiple stages. Some or all of these sub-steps or stages may be executed at the same time, or each of these sub-steps or stages may be executed at different times. In scenarios where execution times differ, the execution order of these sub-steps or stages may be flexibly set according to requirements, and this is not limited to the embodiments of the present disclosure.

[0270] The above specifications and drawings are provided merely as examples to help the reader understand the present disclosure. They are not intended to, and should not be interpreted, as limiting the scope of the present disclosure in any way. While specific embodiments and examples have been provided based on the content disclosed herein, it will be obvious to those skilled in the art that the exemplified embodiments and examples may be modified without departing from the scope of the present disclosure. Adopting other similar means of implementation based on the technical spirit of the present disclosure also falls within the scope of protection of the embodiments of the present disclosure.

Claims

Claim 1 A method performed by a device in a wireless communication system, the method comprising: transmitting a first signal; receiving an echo signal of the first signal; and obtaining a first clutter estimation result based on at least two groups of first channel estimation results, wherein the at least two groups of first channel estimation results are obtained by performing channel estimation based on the echo signal. A method comprising the step of obtaining a second channel estimation result by performing clutter removal on at least two groups of first channel estimation results based on the first clutter estimation result, wherein the at least two groups of first channel estimation results are obtained by: performing channel estimation on the echo signal to obtain a third channel estimation result, and dividing at least one third channel estimation result obtained at each interval of a preset interval value among the third channel estimation results into the same group to obtain the at least two groups of first channel estimation results obtained by the division of the channel estimation results; and dividing at least one echo signal obtained at each interval of the preset interval value among the echo signals into the same group to obtain at least two groups of echo signals, and performing channel estimation on the at least two groups of echo signals to obtain the at least two groups of first channel estimation results obtained by the division of the echo signals. Claim 2 A method according to claim 1, wherein the interval value is determined based on the Doppler frequency distribution of non-target objects. Claim 3 The method of claim 1 further comprises: a step of performing target detection based on at least one of the second channel estimation result and the fourth channel estimation result by performing clutter estimation based on at least one of the first signal and the third channel estimation result to obtain a second clutter estimation result, and performing clutter removal on the third channel estimation result based on the second clutter estimation result to obtain a fourth channel estimation result; and a step of performing at least one of performing target detection based on at least one of the second channel estimation result and the fifth channel estimation result by performing clutter estimation based on at least one of the at least two groups of first channel estimation results obtained by splitting the first signal and the echo signal to obtain a third clutter estimation result, and performing clutter removal on the at least two groups of first channel estimation results obtained by splitting the echo signal based on the third clutter estimation result to obtain a fifth channel estimation result. Claim 4 In claim 3, the step of obtaining a second clutter estimation result by performing clutter estimation based on at least one of the first signal and the third channel estimation result, and obtaining a fourth channel estimation result by performing clutter removal on the third channel estimation result based on the second clutter estimation result comprises: a step of constructing a first matrix of a clutter subspace based on the frequency domain signal of the first signal and at least one of the third channel estimation result; a step of obtaining a reconstructed second clutter estimation result by performing signal reconstruction based on the first matrix and the third channel estimation result; The method includes the step of obtaining the fourth channel estimation result by performing clutter removal on the third channel estimation result based on the second clutter estimation result; and the step of obtaining the third clutter estimation result by performing clutter estimation based on at least one of the at least two groups of first channel estimation results obtained by splitting the first signal and the echo signal, and obtaining the fifth channel estimation result by performing clutter removal on the at least two groups of first channel estimation results obtained by splitting the echo signal based on the third clutter estimation result, comprising: the step of constructing a second matrix of the clutter subspace based on at least one of the at least two groups of first channel estimation results obtained by splitting the frequency domain signal of the first signal and the echo signal; and the step of performing signal reconstruction based on the second matrix and the at least two groups of first channel estimation results obtained by splitting the echo signal to obtain the reconstructed third clutter estimation result. A method comprising the step of obtaining a fifth channel estimation result by performing clutter removal on the first channel estimation result of at least two groups obtained by splitting the echo signal based on the third clutter estimation result. Claim 5 In claim 4, the method comprises: determining whether target detection based on the fourth channel estimation result or the fifth channel estimation result satisfies a first condition; if the first condition is satisfied, constructing a third matrix of the clutter subspace based on the result of the target detection; performing signal reconstruction based on the third matrix and the third channel estimation result to obtain a reconstructed fourth clutter estimation result; or performing signal reconstruction based on the third matrix and the first channel estimation result of at least two groups obtained by splitting the echo signal to obtain a fifth clutter estimation result; and performing clutter removal on the third channel estimation result based on the fourth clutter estimation result to obtain a sixth channel estimation result;Alternatively, the method further comprises the step of obtaining a seventh channel estimation result by performing clutter removal on the first channel estimation results of at least two groups obtained by splitting the echo signal based on the fifth clutter estimation result, wherein the first condition is: that the power of the fourth channel estimation result or the fifth channel estimation result of the target object is detected to be greater than the power of the noise floor, and the detected Doppler frequency of the target object is not equal to zero; that the power of the fourth channel estimation result or the fifth channel estimation result of the target object is detected to be greater than the power of the noise floor, and the detected Doppler frequency of the target object is an integer multiple of the non-zero Doppler resolution; that the power of the fourth channel estimation result or the fifth channel estimation result of the target object corresponding to at least one of a preset distance and a preset angle is detected to be greater than the power of the noise floor, and the detected Doppler frequency of the target object is not equal to zero; and that the fourth of the target object corresponding to at least one of the preset distance and a preset angle A method comprising at least one of the following: the power of the channel estimation result or the fifth channel estimation result is detected to be greater than the power of the noise floor, and the detected Doppler frequency of the target object is an integer multiple of the non-zero Doppler resolution. Claim 6 In claim 3, determining to perform clutter estimation based on the second channel estimation result comprises: determining whether the second channel estimation result satisfies a preset second condition; determining to perform clutter estimation if the second channel estimation result satisfies the second condition; and performing target detection based on the second channel estimation result if the second channel estimation result does not satisfy the second condition, wherein the second condition comprises: the power of the noise floor of the second channel estimation result is greater than or equal to a preset threshold; the power of the channel estimation result corresponding to the zero Doppler frequency within the second channel estimation result is greater than or equal to the preset threshold; the power of the noise floor corresponding to at least one of a preset distance and a preset angle within the second channel estimation result is greater than or equal to the preset threshold; and at least one of the power of the channel estimation result corresponding to the zero Doppler frequency corresponding to at least one of a preset distance and a preset angle within the second channel estimation result is greater than or equal to the preset threshold. Claim 7 A method according to claim 6, wherein the preset threshold is related to at least one of the distance of a detected target object or the radar cross section (RCS) of the target object. Claim 8 As a device in a wireless communication system, a transceiver; The device comprises a controller connected to the transceiver, wherein the controller is configured to cause the device to: transmit a first signal; receive an echo signal of the first signal; obtain a first clutter estimation result based on at least two groups of first channel estimation results, wherein the at least two groups of first channel estimation results are obtained by performing channel estimation based on the echo signal; and perform clutter removal on the at least two groups of first channel estimation results based on the first clutter estimation result to obtain a second channel estimation result, wherein the at least two groups of first channel estimation results are configured to: obtain a third channel estimation result by performing channel estimation on the echo signal; divide at least one third channel estimation result obtained at each interval of a preset interval value among the third channel estimation results into the same group to obtain the at least two groups of first channel estimation results obtained by the division of the channel estimation results; and divide at least one echo signal obtained at each interval of the preset interval value among the echo signals into the same group to obtain at least two groups of echo signals, wherein the at least A device obtained by at least one of the operations of performing channel estimation on two groups of echo signals and obtaining the first channel estimation results of at least two groups obtained by splitting the echo signals. Claim 9 In claim 8, the device wherein the interval value is determined based on the Doppler frequency distribution of a non-target object. Claim 10 In claim 8, the device is further configured such that, based on deciding to perform clutter estimation based on the second channel estimation result: performing clutter estimation based on at least one of the first signal and the third channel estimation result to obtain a second clutter estimation result, and performing clutter removal on the third channel estimation result based on the second clutter estimation result to obtain a fourth channel estimation result, thereby performing target detection based on at least one of the second channel estimation result and the fourth channel estimation result, and performing clutter estimation based on at least one of the at least two groups of first channel estimation results obtained by splitting the first signal and the echo signal to obtain a third clutter estimation result, and performing clutter removal on the at least two groups of first channel estimation results obtained by splitting the echo signal based on the third clutter estimation result to obtain a fifth channel estimation result, thereby performing target detection based on at least one of the second channel estimation result and the fifth channel estimation result. Claim 11 In claim 10, performing clutter estimation based on at least one of the first signal and the third channel estimation result to obtain a second clutter estimation result, and performing clutter removal on the third channel estimation result based on the second clutter estimation result to obtain a fourth channel estimation result comprises: constructing a first matrix of a clutter subspace based on the frequency domain signal of the first signal and at least one of the third channel estimation result; performing signal reconstruction based on the first matrix and the third channel estimation result to obtain a reconstructed second clutter estimation result; and performing clutter removal on the third channel estimation result based on the second clutter estimation result to obtain the fourth channel estimation result, and performing clutter estimation based on at least one of the at least two groups of first channel estimation results obtained by splitting the first signal and the echo signal to obtain a third clutter estimation result, and based on the third clutter estimation result, the at least two groups of first channel estimation results obtained by splitting the echo signal A device for obtaining a fifth channel estimation result by performing clutter removal on the first channel estimation result, comprising: constructing a second matrix of a clutter subspace based on at least one of at least two groups of first channel estimation results obtained by splitting the frequency domain signal of the first signal and the echo signal; performing signal reconstruction based on the second matrix and the at least two groups of first channel estimation results obtained by splitting the echo signal to obtain a reconstructed third clutter estimation result; and performing clutter removal on the at least two groups of first channel estimation results obtained by splitting the echo signal based on the third clutter estimation result to obtain the fifth channel estimation result. Claim 12 In claim 11, the controller causes the device to: determine whether target detection based on the fourth channel estimation result or the fifth channel estimation result satisfies a first condition; if the first condition is satisfied, construct a third matrix of the clutter subspace based on the result of the target detection, and perform signal reconstruction based on the third matrix and the third channel estimation result to obtain a reconstructed fourth clutter estimation result; or perform signal reconstruction based on the third matrix and the first channel estimation result of at least two groups obtained by splitting the echo signal to obtain a fifth clutter estimation result, and perform clutter removal on the third channel estimation result based on the fourth clutter estimation result to obtain a sixth channel estimation result;Alternatively, it is further configured to obtain a seventh channel estimation result by performing clutter removal on the at least two groups of first channel estimation results obtained by splitting the echo signal based on the fifth clutter estimation result, wherein the first condition is: that the power of the fourth channel estimation result or the fifth channel estimation result of the target object is detected to be greater than the power of the noise floor, and the detected Doppler frequency of the target object is not equal to zero; that the power of the fourth channel estimation result or the fifth channel estimation result of the target object is detected to be greater than the power of the noise floor, and the detected Doppler frequency of the target object is an integer multiple of the non-zero Doppler resolution; that the power of the fourth channel estimation result or the fifth channel estimation result of the target object corresponding to at least one of a preset distance and a preset angle is detected to be greater than the power of the noise floor, and the detected Doppler frequency of the target object is not equal to zero; and that the fourth channel estimation result or the fifth channel estimation result of the target object corresponding to at least one of the preset distance and a preset angle A device comprising at least one of the following: the power of the result is detected to be greater than the power of the noise floor, and the detected Doppler frequency of the target object is an integer multiple of the non-zero Doppler resolution. Claim 13 In claim 10, determining to perform clutter estimation based on the second channel estimation result comprises: determining whether the second channel estimation result satisfies a preset second condition; determining to perform clutter estimation if the second channel estimation result satisfies the second condition; and performing target detection based on the second channel estimation result if the second channel estimation result does not satisfy the second condition, wherein the second condition comprises: the power of the noise floor of the second channel estimation result is greater than or equal to a preset threshold; the power of the channel estimation result corresponding to the zero Doppler frequency within the second channel estimation result is greater than or equal to the preset threshold; the power of the noise floor corresponding to at least one of a preset distance and a preset angle within the second channel estimation result is greater than or equal to the preset threshold; and the power of the channel estimation result corresponding to the zero Doppler frequency corresponding to at least one of a preset distance and a preset angle within the second channel estimation result is greater than or equal to the preset threshold. Claim 14 A device according to claim 13, wherein the preset threshold is related to at least one of the distance of a detected target object or the radar cross section (RCS) of the target object.

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