Method and apparatus for performing sensing an object 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 method performed by a first node in a wireless communication system and the first node, the method proposing a new clutter removal solution, including: transmitting a first signal, receiving echo signals of the first signal, and performing channel estimation based on the echo signals, to acquire at least two groups of first channel estimation results obtained by dividing the channel estimation results or dividing the echo signals; acquiring first clutter estimation results based on the at least two groups of first channel estimation results; and performing clutter removal on the at least two groups of first channel estimation results based on the first clutter estimation results to obtain second channel estimation results. Implementations of the present disclosure can obtain clutter estimation results based on grouped channel estimation results and then perform clutter removal, which can effectively reduce the delay and computational complexity of clutter estimation and improve the efficiency of clutter estimation.

Description

METHOD AND APPARATUS FOR PERFORMING SENSING AN OBJECT BASED ON CLUTTER ESTIMATION AND REMOVAL IN A WIRELESS COMMUNICATION SYSTEM

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

[0002] Considering the development of wireless communication from generation to generation, the technologies have been developed mainly for services targeting humans, such as voice calls, multimedia services, and data services. With the commercialization of 5th-generation (5G) communication systems, it is expected that the number of connected devices will exponentially grow. Increasingly, these will be connected to communication networks. Examples of internet-of-things may include vehicles, robots, unmanned aerial vehicles, home appliances, displays, smart sensors connected to various infrastructures, construction machines, and factory equipment. Mobile devices are expected to evolve in various form-factors, such as augmented reality glasses, virtual reality headsets, and hologram devices. In order to provide various services by connecting hundreds of billions of devices and things in the 6th-generation (6G) era, there have been ongoing efforts to develop improved 6G communication systems. For these reasons, 6G communication systems are referred to as beyond-5G systems.

[0003] 6G communication systems, which are expected to be commercialized around 2030, will have a peak data rate of tera (1,000 giga)-level bps and a radio latency less than 100μsec, and thus will be 50 times as fast as 5G communication systems and have the 1 / 10 radio latency thereof.

[0004] In order to accomplish such a high data rate and an ultra-low latency, it has been considered to implement 6G communication systems in a terahertz band (for example, 95GHz to 3THz bands). It is expected that, due to severer path loss and atmospheric absorption in the terahertz bands than those in millimeter wave (mmWave) bands introduced in 5G, technologies capable of securing the signal transmission distance (that is, coverage) will become more crucial. It is necessary to develop, as major technologies for securing the coverage, radio frequency (RF) elements, antennas, novel waveforms having a better coverage than orthogonal frequency division multiplexing (OFDM), beamforming and massive multiple input multiple output (MIMO), full dimensional MIMO (FD-MIMO), array antennas, and multi-antenna transmission technologies such as large-scale antennas. In addition, there has been ongoing discussion on new technologies for improving the coverage of terahertz-band signals, such as metamaterial-based lenses and antennas, orbital angular momentum (OAM), and reconfigurable intelligence surface (RIS).

[0005] Moreover, in order to improve the spectral efficiency and the overall network performances, the following technologies have been developed for 6G communication systems: a full-duplex technology for enabling an uplink transmission and a downlink transmission to use the same frequency resource simultaneously; a network technology for utilizing satellites, high-altitude platform stations (HAPS), and the like in an integrated manner; an improved network structure for supporting mobile base stations and the like and enabling network operation optimization and automation and the like possible; a dynamic spectrum sharing technology via collision avoidance based on a prediction of spectrum usage; an use of artificial intelligence (AI) in wireless communication for improvement of overall network operation by utilizing AI from a designing phase for developing 6G and internalizing end-to-end AI support functions; and a next-generation distributed computing technology for overcoming the limit of user equipment (UE) computing ability through reachable super-high-performance communication and computing resources (such as mobile edge computing (MEC), clouds, and the like) over the network. In addition, by designing new protocols to be used in 6G communication systems, developing mechanisms for implementing a hardware-based security environment and safe use of data, and developing technologies for maintaining privacy, attempts to strengthen the connectivity between devices, optimization of the network, promotion of softwarization of network entities, and increase in the openness of wireless communications are continuing.

[0006] It is expected that research and development of 6G communication systems in hyper-connectivity, including person to machine (P2M) as well as machine to machine (M2M), will bring the next hyper-connected experience. Particularly, it is expected that services such as truly immersive extended reality (XR), high-fidelity mobile hologram, and digital replica could be provided through 6G communication systems. In addition, services such as remote surgery for security and reliability enhancement, industrial automation, and emergency response will be provided through the 6G communication system such that the technologies could be applied in various fields such as industry, medical care, automobiles, and home appliances.

[0007] The present disclosure relates to a method and apparatus for performing sensing based on clutter estimation and removal in a wireless communication system.

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

[0009] In one aspect, embodiments of the present disclosure provide a method performed by a first node in a communication system, the method including:

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

[0011] acquiring first clutter estimation results based on the at least two groups of first channel estimation results; and

[0012] performing clutter removal on the at least two groups of first channel estimation results based on the first clutter estimation results to obtain second channel estimation results.

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

[0014] performing channel estimation on the echo signals to acquire third channel estimation results, and dividing at least one third channel estimation result obtained at each interval of a preset interval value from among the third channel estimation results into a same group, to acquire the at least two groups of first channel estimation results obtained by dividing the channel estimation results; and

[0015] dividing at least one echo signal obtained at each interval of the preset interval value from among the echo signals into a same group to acquire at least two groups of echo signals, and performing channel estimation on the at least two groups of echo signals, to acquire the 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 a Doppler frequency distribution of non-target objects.

[0017] In a possible embodiment, the method further includes upon determination to perform clutter estimation based on the second channel estimation results, performing at least one of the following:

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

[0019] performing clutter estimation based on at least one of the first signal and the at least two groups of first channel estimation results obtained by dividing the echo signals to obtain third clutter estimation results, and performing clutter removal on the at least two groups of first channel estimation results obtained by dividing the echo signals based on the third clutter estimation results to obtain fifth channel estimation results, to perform target detection based on at least one of the second channel estimation results and the fifth channel estimation results.

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

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

[0022] performing signal reconstruction based on the first matrix and the third channel estimation results to acquire reconstructed second clutter estimation results; and

[0023] performing clutter removal on the third channel estimation results based on the second clutter estimation results to obtain the fourth channel estimation results; and

[0024] performing clutter estimation based on at least one of the first signal and the at least two groups of first channel estimation results obtained by dividing the echo signals to obtain third clutter estimation results, and performing clutter removal on the at least two groups of first channel estimation results obtained by dividing the echo signals based on the third clutter estimation results to obtain fifth channel estimation results includes:

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

[0026] performing signal reconstruction based on the second matrix and the at least two groups of first channel estimation results obtained by dividing the echo signals to acquire reconstructed third clutter estimation results; and

[0027] performing, based on the third clutter estimation results, clutter removal on the at least two groups of first channel estimation results obtained by dividing the echo signals, to obtain the fifth channel estimation results.

[0028] In a possible embodiment, the method further includes:

[0029] determining whether the target detection based on the fourth channel estimation results or the fifth channel estimation results satisfies a first condition;

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

[0031] performing signal reconstruction based on the third matrix and the third channel estimation results to acquire reconstructed fourth clutter estimation results; or performing signal reconstruction based on the third matrix and the at least two groups of first channel estimation results obtained by dividing the echo signals, to obtain fifth clutter estimation results; and

[0032] performing clutter removal on the third channel estimation results based on the fourth clutter estimation results to obtain sixth channel estimation results; or performing clutter removal on the at least two groups of first channel estimation results obtained by dividing the echo signals based on the fifth clutter estimation results, to obtain a seventh channel estimation results.

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

[0034] it is detected that the power of the fourth channel estimation results or the fifth channel estimation results of a target object is greater than the power of noise floor, and a detected Doppler frequency of the target object is not equal to 0;

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

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

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

[0038] In a possible embodiment, the determination to perform clutter estimation based on the second channel estimation results includes:

[0039] determining whether the second channel estimation results satisfy a preset second condition;

[0040] determining to perform clutter estimation if the second channel estimation results satisfy the second condition; and

[0041] performing target detection based on the second channel estimation results if the second channel estimation results do not satisfy the second condition.

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

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

[0044] a power of a channel estimation results corresponding to a zero Doppler frequency in the second channel estimation results is greater than or equal to the preset threshold value;

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

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

[0047] In a possible embodiment, the preset threshold value is related to a detected distance of a target object and / or Radar Cross Section (RCS) of the target object.

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

[0049] In another aspect, embodiments of the present disclosure also provide a computer-readable storage medium having stored therein computer programs that, when executed by a processor, perform a method provided by any of the embodiments of the present disclosure.

[0050] In another aspect, there is provided a computer program product including computer programs which when executed by a processor perform a method as provided in any of the optional embodiments of the present disclosure.

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

[0052] Aspects of the present disclosure provide efficient communication methods in a wireless communication system.

[0053] Fig. 1 illustrates a structural diagram of a wireless network system to which an embodiment of the present disclosure is applicable.

[0054] Fig. 2 illustrates a structural diagram of an example base station according to the present disclosure.

[0055] Fig. 3 illustrates a structural diagram of example user equipment according to the present disclosure.

[0056] Fig. 4 illustrates a flow diagram of a method performed by a first node provided by an embodiment of the present disclosure.

[0057] Fig. 5 illustrates a flow diagram of a method for clutter estimation and clutter removal according to an embodiment of the present disclosure.

[0058] Fig. 6 illustrates a flow diagram of a method for first clutter estimation according to an embodiment of the present disclosure.

[0059] Fig. 7 illustrates a diagram of grouping channel estimation results according to an embodiment of the present disclosure.

[0060] Fig. 8 illustrates a flow diagram of a method for clutter removal according to an embodiment of the present disclosure.

[0061] Fig. 9 illustrates a diagram of arranging channel estimation results according to an embodiment of the present disclosure.

[0062] Fig. 10 illustrates a flow diagram of another method for clutter estimation and clutter removal according to an embodiment of the present disclosure.

[0063] Fig. 11 illustrates a flow diagram of a method for dynamically determining whether to perform clutter estimation and clutter removal according to an embodiment of the present disclosure.

[0064] Fig. 12 illustrates a structural diagram of an electronic device according to an embodiment of the present disclosure.

[0065] Fig. 13 illustrates the configuration of a UE in a wireless communication system according to various embodiments.

[0066] Fig. 14 illustrates the configuration of a base station or a network entity in a wireless communication system according to various embodiments.

[0067] Throughout the drawings, it should be noted that like reference numbers are used to depict the same or similar elements, features, and structures.

[0068] Before undertaking the Mode for Invention below, it may be advantageous to set forth definitions of certain words and phrases used throughout this patent document.

[0069] The term “connect” and its derivatives refer to any direct or indirect communication between two or more elements, whether those elements are in physical contact with one another.

[0070] The terms “transmit,” “receive,” and “communicate,” as well as derivatives thereof, encompass both direct and indirect communication.

[0071] The terms “include” and “comprise,” as well as derivatives thereof, mean inclusion without limitation.

[0072] The term “or” is inclusive, meaning and / or.

[0073] The phrase “associated with,” as well as derivatives thereof, means to include, be included within, interconnect with, contain, be contained within, connect to or with, couple to or with, be communicable with, cooperate with, interleave, juxtapose, be proximate to, be bound to or with, have, have a property of, have a relationship to or with, or the like.

[0074] 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 a combination of hardware and software and / or firmware. The functionality associated with any particular controller may be centralized or distributed, whether locally or remotely.

[0075] The phrase “at least one of,” when used with a list of items, means that different combinations of one or more of the listed items may be used, and only one item in the list may be needed. For example, “at least one of A, B, and C” includes any of the following combinations: A, B, C, A and B, A and C, B and C, and A and B and C. Likewise, the term “set” means one or more. Accordingly, a set of items can be a single item or a collection of two or more items.

[0076] It is to be understood that the singular forms “a,” “an,” and “the” include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to “a component surface” includes reference to one or more of such surfaces.

[0077] Moreover, various functions described below can be implemented or supported by one or more computer programs, each of which is formed from computer readable program code and embodied in a computer readable medium. The terms “application” and “program” refer to one or more computer programs, software components, sets of instructions, procedures, functions, objects, classes, instances, related data, or a portion thereof adapted for implementation in a suitable 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 capable of being accessed by a computer, such as read only memory (ROM), random access memory (RAM), a hard disk drive, a compact disc (CD), a digital video disc (DVD), or any other type of memory. A “non-transitory” computer readable medium excludes wired, wireless, optical, or other communication links that transport transitory electrical or other signals. A non-transitory computer readable medium includes media where data can be permanently stored and media where data can be stored and later overwritten, such as a rewritable optical disc or an erasable memory device.

[0078] Definitions for other certain words and phrases are provided throughout the present disclosure. Those of ordinary skill in the art should understand that in many if not most instances, such definitions apply to prior as well as future uses of such defined words and phrases.

[0079] The figures included herein, and the various embodiments used to describe the principles of the present disclosure are by way of illustration only and should not be construed in any way to limit the scope of the disclosure. Further, those skilled in the art will understand that the principles of the present disclosure may be implemented in any suitably arranged wireless communication system.

[0080] FIGS. 1-3 below describe various embodiments of the present disclosure implemented in wireless communications systems. The descriptions of FIGS. 1-3 are not meant to imply physical or architectural limitations to the manner in which different embodiments may be implemented. Different embodiments of the present disclosure may be implemented in any suitably-arranged communications system.

[0081] FIG. 1 illustrates an example wireless network according to embodiments of the present disclosure. The embodiment of the wireless network shown in FIG. 1 is for illustration only. Other embodiments of the wireless network 100 could be used without departing from the scope of the present disclosure.

[0082] As shown 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 other data network.

[0083] The gNB 102 provides wireless broadband access to the network 130 for a first plurality of user equipments (UEs) within a coverage area 120 of the gNB 102. The first plurality of UEs includes a UE 111, which may be located in a small business; a UE 112, which may be located in an enterprise (E); a UE 113, which may be located in a WiFi hotspot (HS); a UE 114, which may be located in a first residence (R1); a UE 115, which may be located in a second residence (R2); and a UE 116, which may be a mobile device (M), such as a cell phone, a wireless laptop, a wireless personal digital assistant (PDA), or the like. The gNB 103 provides wireless broadband access to the network 130 for a second plurality of UEs within a coverage area 125 of the gNB 103. The second plurality of UEs includes the UE 115 and the UE 116, as well as subscriber stations (SS, for example, UEs) 117, 118 and 119. In some embodiments, one or more of the gNBs 101-103 may communicate with each other and with the UEs 111-116 using existing wireless communication techniques, and one or more of the UE 111-119 may communicate directly with each other (e.g., UEs 117-119) using other existing or proposed wireless communication techniques.

[0084] Depending on the network type, the term “base station” or “BS” can refer to any component (or collection of components) configured to provide wireless access to a network, such as transmit point (TP), transmit-receive point (TRP), an enhanced (or “evolved”) base station (eNodeB or eNB), a 5G base station (gNB), a macrocell, a femtocell, a wireless fidelity (WiFi) access point (AP), or other wirelessly enabled devices. Base stations may provide wireless access in accordance with one or more wireless communication protocols, e.g., 3GPP 5G New Radio (NR), Long Term Evolution (LTE), LTE Advanced (LTE-A), high speed packet access (HSPA), Wi-Fi 802.11a / b / g / n / ac, etc. For the sake of convenience, the various names for a base station-type apparatus and functionality are used interchangeably in this patent document to refer to network infrastructure components that provide wireless access to remote terminals. Also, depending on the network type, the term “user equipment” (UE) can refer to any component such as a mobile station (MS), subscriber station (SS), remote terminal, wireless terminal, receive point, or user device. For the sake of convenience, the various names for a user equipment-type device and functionality are used interchangeably in this patent document to refer to remote wireless equipment that wirelessly accesses a BS, whether the UE is a mobile device (such as a mobile telephone or smartphone) or is normally considered a stationary device (such as a desktop computer or vending machine).

[0085] Dotted lines show the approximate extents of the coverage areas 120 and 125, which are shown as approximately circular for the purposes of illustration and explanation only. It should be clearly understood that the coverage areas associated with gNBs, such as the coverage areas 120 and 125, may have other shapes, including irregular shapes, depending upon the configuration of the gNBs and variations in the radio environment associated with natural and man-made obstructions.

[0086] As described in more detail below, one or more of the UEs 111-119 include circuitry, programing, or a combination thereof. In certain embodiments, and one or more of the gNBs 101-103 includes circuitry, programing, or a combination thereof.

[0087] Although FIG. 1 illustrates one example of a wireless network, various changes may be made to FIG. 1. For example, the wireless network 100 could include any number of gNBs and any number of UEs in any suitable arrangement. Also, the gNB 101 could communicate directly with any number of UEs and provide those UEs with wireless broadband access to the network 130. Similarly, each gNB 102-103 could communicate directly with the network 130 and provide UEs with direct wireless broadband access to the network 130. Further, the gNBs 101, 102, and / or 103 could provide access to other or additional external networks, such as external telephone networks or other types of data networks.

[0088] FIG. 2 illustrates an example base station according to embodiments of the present disclosure. The embodiment of the gNB 102 illustrated in FIG. 2 is for illustration only, and the gNBs 101 and 103 of FIG. 1 could have the same or similar configuration. However, gNBs come in a wide variety of configurations, and FIG. 2 does not limit the scope of the present disclosure to any particular implementation of a gNB.

[0089] As shown in FIG 2, the gNB 102 includes multiple antennas 200a-200n, multiple radio frequency (RF) transceivers 201a-201n, transmit (TX) processing circuitry 203, and receive (RX) processing circuitry 204. The gNB 102 also includes a controller / processor 205, a memory 206, and a backhaul or network interface 207.

[0090] The RF transceivers 201a-201n receive, from the antennas 200a-200n, incoming RF signals, such as signals transmitted by UEs in the network 100. The RF transceivers 201a-201n down-convert the incoming RF signals to generate intermediate frequency (IF) or baseband signals. The IF or baseband signals are transmitted to the RX processing circuitry 204, which generates processed baseband signals by filtering, decoding, and / or digitizing the baseband or IF signals. The RX processing circuitry 204 transmits the processed baseband signals to the controller / processor 205 for further processing.

[0091] The TX processing circuitry 203 receives analog or digital data (such as voice data, web data, electronic mail, or interactive video game data) from the controller / processor 205. The TX processing circuitry 203 encodes, multiplexes, and / or digitizes the outgoing baseband data to generate processed baseband or IF signals. The RF transceivers 201a-201n receive the outgoing processed baseband or IF signals from the TX processing circuitry 203 and up-converts the baseband or IF signals to RF signals that are transmitted via the antennas 201a-201n.

[0092] The controller / processor 205 can include one or more processors or other processing devices that control the overall operation of the gNB 102. For example, the controller / processor 205 could control the reception of forward channel signals and the transmission of reverse channel signals by the RF transceivers 201a-201n, the RX processing circuitry 204, and the TX processing circuitry 203 in accordance with well-known principles. The controller / processor 205 could support additional functions as well, such as more advanced wireless communication functions.

[0093] For instance, the controller / processor 205 could support beam forming or directional routing operations in which outgoing signals from multiple antennas 200a-200n are weighted differently to effectively steer the outgoing signals in a desired direction. Any of a wide variety of other functions could be supported in the gNB 102 by the controller / processor 205.

[0094] The controller / processor 205 is also capable of executing programs and other processes resident in the memory 206, such as an operating system (OS). The controller / processor 205 can move data into or out of the memory 206 as required by an executing process.

[0095] The controller / processor 205 is also coupled to the backhaul or network interface 207. The backhaul or network interface 207 allows the gNB 102 to communicate with other devices or systems over a backhaul connection or over a network. The interface 207 could support communications over any suitable wired or wireless connection(s). For example, when the gNB 102 is implemented as part of a cellular communication system (such as one supporting 5G, LTE, or LTE-A), the interface 207 could allow the gNB 102 to communicate with other gNBs over a wired or wireless backhaul connection. When the gNB 102 is implemented as an access point, the interface 207 could allow the gNB 102 to communicate over a wired or wireless local area network or over a wired or wireless connection to a larger network (such as the Internet). The interface 207 includes any suitable structure supporting communications over a wired or wireless connection, such as an Ethernet or RF transceiver.

[0096] The memory 206 is coupled to the controller / processor 205. Part of the memory 206 could include a random access memory (RAM), and another part of the memory 206 could include a Flash memory or other read only memory (ROM).

[0097] Although FIG. 2 illustrates one example of gNB 102, various changes may be made to FIG. 2. For example, the gNB 102 could include any number of each component shown in FIG. 2. As a particular example, an access point could include a number of interfaces 207, and the controller / processor 205 could support routing functions to route data between different network addresses. As another particular example, while shown as including a single instance of TX processing circuitry 203 and a single instance of RX processing circuitry 204, the gNB 102 could include multiple instances of each (such as one per RF transceiver). Also, various components in FIG. 2 could be combined, further subdivided, or omitted and additional components could be added according to particular needs.

[0098] FIG. 3 illustrates an example user equipment according to embodiments of the present disclosure. The embodiment of the UE 116 illustrated in FIG. 3 is for illustration only, and the UEs 111-115 and 117-119 of FIG. 1 could have the same or similar configuration. However, UEs come in a wide variety of configurations, and FIG. 3 does not limit the scope of the present disclosure to any particular implementation of a UE.

[0099] As shown in FIG. 3, the UE 116 includes an antenna 301, a radio frequency (RF) transceiver 302, TX processing circuitry 303, a microphone 304, and receive (RX) processing circuitry 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.

[0100] The RF transceiver 302 receives, from the antenna 301, an incoming RF signal transmitted by an gNB of the network 100. 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 the RX processing circuitry 305, which generates a processed baseband signal by filtering, decoding, and / or digitizing the baseband or IF signal. The RX processing circuitry 305 transmits the processed baseband signal to the speaker 306 (such as for voice data) or to the processor 307 for further processing (such as for web browsing data).

[0101] The TX processing circuitry 303 receives analog or digital voice data from the microphone 304 or other outgoing baseband data (such as web data, e-mail, or interactive video game data) from the processor 307. The TX processing circuitry 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 circuitry 303 and up-converts the baseband or IF signal to an RF signal that is transmitted via the antenna 301.

[0102] The processor 307 can include one or more processors or other processing devices and execute the OS 312 stored in the memory 311 in order to control the overall operation of the UE 116. For example, the processor 307 could control the reception of forward channel signals and the transmission of reverse channel signals by the RF transceiver 302, the RX processing circuitry 305, and the TX processing circuitry 303 in accordance with well-known principles. In some embodiments, the processor 307 includes at least one microprocessor or microcontroller.

[0103] The processor 307 is also capable of executing other processes and programs resident in the memory 311, such as processes for CSI reporting on uplink channel. The processor 307 can move data into or out of the memory 311 as required by an executing process. In some embodiments, the processor 307 is configured to execute the applications 313 based on the OS 312 or in response to signals received from gNBs or an operator. The processor 307 is also coupled to the I / O interface 308, which 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 the communication path between these accessories and the processor 307.

[0104] The processor 307 is also coupled to the touchscreen display 310. The user of the UE 116 can use the touchscreen display 310 to enter data into the UE 116. The touchscreen display 310 may be a liquid crystal display, light emitting diode display, or other display capable of rendering text and / or at least limited graphics, such as from web sites.

[0105] The memory 311 is coupled to the processor 307. Part of the memory 311 could include RAM, and another part of the memory 311 could include a Flash memory or other ROM.

[0106] Although FIG. 3 illustrates one example of UE 116, various changes may be made to FIG. 3. For example, various components in FIG. 3 could be combined, further subdivided, or omitted and additional components could be added according to particular needs. As a particular example, the processor 307 could be divided into multiple processors, such as one or more central processing units (CPUs) and one or more graphics processing units (GPUs). Also, while FIG. 3 illustrates the UE 116 configured as a mobile telephone or smartphone, UEs could be configured to operate as other types of mobile or stationary devices.

[0107] With advances in science and technology, the variety of communication devices is increasing. In addition to traditional cell phones, computers, etc. mobile robots may be included, such as autonomous driving vehicles and unmanned aerial vehicles. Mobile devices of this type often need to be or can be accurately positioned to accurately identify the current situation and to react, i.e. to have positioning capabilities like those provided by radar technology. A straightforward approach may be to equip the communication device with a radar module, however, as the operating frequency band of the communication system has evolved to a higher frequency band in recent years, the communication frequency band has approached to the radar frequency band gradually, and the resulting interference and resource conflicts between the communication system and the radar system will not be avoided. One idea to solve this problem may be to consider a fusion system of communication and radar, known as integrated sensing and communication (ISAC), to further enhance the functionality of the communication system and improve spectral efficiency. At present, the ISAC is one of the key technologies of future communication systems in both industrial and academic circles.

[0108] The core idea of the ISAC is to use the same set of hardware devices, on the basis of ensuring basic communication functions, to achieve the sensing of the surrounding environment at the cost of as few resources as possible. That is, a communication node (e.g. a gNB, a UE, a repeater, and an integrated access and backhaul (IAB) base station) in a communication system can simultaneously have the functions of communication and sensing, and can be referred to as an ISAC node, and is hereinafter referred to as a communication and sensing node. A sensing function is added in a communication system, and a feasible solution is that a first communication and sensing node (which may also be referred to as a first node) receives a signal for sensing (hereinafter referred to as a sensing signal) transmitted by a second communication and sensing node (which may also be referred to as a second node), and obtains features of a sensed target object according to signal detection on the sensing signal. Since the sensing signal is reflected by the sensed target object in the environment, the frequency response of the propagation channel will change correspondingly, and the change of frequency response has a corresponding relationship with the distance and moving speed of the sensed target object, so the first communication and sensing node can estimate the propagation channel according to the received echo signal, to obtain the features of the sensed target object. The features of the sensed target objects may include but are not limited to, the number of the sensed target objects, the distance between a sensed target object and the communication and sensing node, the radial speed of the sensed target object, etc.; and, the sensed target object may be an object that accesses a communication network (e.g. a base station and a terminal) or an object that does not access a communication network (e.g. a small UAV, a building, an animal, and a plant).

[0109] In the above-mentioned communication and sensing solution, a first communication and sensing node and a second communication and sensing node can be a base station and a user respectively, for example, the first communication and sensing node is a user equipment (UE) and the second communication and sensing node is a serving cell thereof, or the second communication and sensing node is a UE and the first communication and sensing node is a serving cell thereof. According to the sensing requirements, a serving cell can configure UE to transmit or receive a sensing signal. It may correspond to a procedure in which the UE is configured to transmit an uplink sensing signal, and a base station of the serving cell receives the uplink sensing signal and performs sensing measurement, this procedure is hereinafter referred to as uplink sensing for short; and it may correspond to a procedure in which the UE is configured to receive a downlink sensing signal, and performs sensing measurement, this procedure is hereinafter referred to as downlink sensing for short.

[0110] Since both the sensed object and the observation node are usually located on the ground or in a low-altitude environment, the sensing signal received by the communication and sensing node may be affected by the clutter in the environment, seriously degrading the sensing performance; the clutter is caused by the echoes reflected back from scatterers in the environment, such as the ground, buildings, trees, etc.; and since the scatterers causing the clutter are usually not the target objects actually needing to be sensed, the clutter is an interference signal to the echoes of the target objects actually needing to be sensed (such as people, vehicles, and unmanned aerial vehicles).

[0111] For example, when a communication and sensing node is a stationary node (such as a base station, etc.), the clutter interference caused by the ground and surrounding buildings is an important factor affecting the sensing performance of the system, especially for the detection, positioning and tracking of "low, slow, and small" targets as frequently mentioned. In addition to the reflected signal of the target object to be detected in the environment, there are various kinds of clutter reflected from the surrounding buildings and the ground, which would affect the detection of the stationary or low-speed moving target object. When the velocity of the target object is small and the reflected energy is weak, the influence caused by the sidelobes of the static clutter is more serious. If the echo is coherently accumulated without any processing, the sidelobes of clutter may cover the target because they are too strong, which greatly reduces the ability of communication and sensing nodes to detect the target. Therefore, clutter suppression is a key measure to ensure that the communication and sensing node can detect the target object that needs to be sensed, especially the detection of low-speed targets requires higher clutter interference cancellation capability.

[0112] In the prior art, a clutter suppression method can be performed based on accumulated echo data, specifically, after receiving a plurality of groups of echo data, performing processing on the plurality of groups of echo data; however, this method needs to process the received plurality of groups of echo data, so the delay of accumulating echo data is high, and the complexity of processing the plurality of groups of echo data is also high, which seriously affects the efficiency of clutter estimation and the detection of the target. Therefore, how to effectively reduce the delay and computational complexity of clutter estimation and improve the efficiency of clutter estimation is an urgent problem to be solved.

[0113] In the present disclosure, to optimize an ISAC system and solve or improve one or more problems currently existing, a sensing solution (a method executed by a first node in a communication integrated system) is provided to reduce computational complexity and improve the detection capability of sensing a target object. In addition, the solution also proposes a clutter estimation and removal method adapted by the communication and sensing nodes, which can adaptively determine whether to perform non-real-time or real-time clutter estimation; the non-real-time estimation enables the communication and sensing nodes to adapt to the long-term change of clutter, and the real-time estimation can capture the short-term change of clutter. Specifically, in a non-real-time clutter estimation method, echo (environmental clutter) of an environmental background is accumulated, and the clutter feature extraction is performed on the accumulated echo (see Embodiment 2 below for details) , and based on the result (extracted clutter feature) of the non-real-time clutter estimation, clutter components can be reconstructed in real-time, and the clutter components in an echo signal containing the clutter and a sensed target object are effectively removed (see Embodiment 3 below for details), thereby improving the detection performance of the sensed target object. The real-time clutter estimation method is to perform clutter channel estimation in the frequency domain based on real-time accumulated echoes, and then perform real-time clutter reconstruction and removal (see the following Embodiment 4 for details). In addition, the proposed clutter estimation and removal method adapted by the communication and sensing node can also adaptively determine the clutter estimation and removal method based on the result of the first clutter removal using the non-real-time clutter estimation, aiming at improving the detection performance of the target object, specifically, dynamically determining whether to continue to use the echo signal obtained by the first clutter removal using the non-real-time clutter estimation result to detect the target object, or using the real-time clutter estimation and using the real-time clutter estimation result to remove the clutter; then, target object detection is performed based on the first clutter-removed echo signal using the real-time clutter estimation result (see Embodiment 5 below for details). This has the advantage that by combining the non-real-time clutter estimation with the real-time clutter estimation, the communication and sensing node can obtain a more accurate clutter characteristic model, with higher robustness for dynamically changing clutter scenes and environmental conditions, and achieve better clutter removal and the detection capability of the target object.

[0114] The methods provided by embodiments of the present disclosure may be performed by any electronic device / node, such as UE in a wireless communication system or a network node, such as a base station or other network node.

[0115] It should be noted that some of the term names referred to in the embodiments of the present disclosure may use the term names already existing in the communication standard, some of the term names may be newly added or newly defined term names, these terms may be referred to as other names, or may be described in other ways (such as a text description) in the future communication standard. The names or wordings of the various signals / information / matrices / spaces / results referred to in the embodiments of the present disclosure are not exclusive, and the names or wordings of the signals / information / matrices / spaces / results may theoretically be changed as long as the roles, contents, or descriptions of the signals / information / matrices / spaces / results can correspond to or be associated with each other.

[0116] The technical solutions provided by the present disclosure and the technical effects brought about by the technical solutions are explained below through the description of various optional embodiments. In the absence of conflict or contradiction, the following embodiments may be referred to, learned, or combined with each other, and the description of the same terms, similar features, and similar steps in different embodiments will not be repeated. In embodiments that include a plurality of steps, embodiments of the present disclosure do not exclusively limit the order in which the plurality of steps are performed if there is no explicit ordering of the plurality of steps.

[0117] Optional embodiments of the methods provided by the present disclosure are further described below in connection with the principles of solutions provided by the present disclosure and several optional embodiments, the steps of different embodiments may be combined or substituted with each other without conflict.

[0118] Fig. 4 illustrates a method performed by a first node in a wireless communication system according to an embodiment of the present disclosure, which is a clutter estimation method. The first node is a sensing node, and optionally, the first node can be UE, and the first node can also be a base station in a communication system, etc. and as shown in Fig. 4, the method can include S101-S104:

[0119] In according to an embodiment of the present disclosure, at step S101, the method includes transmitting a first signal, receiving echo signals of the first signal, and performing channel estimation based on the echo signals to acquire at least two groups of first channel estimation results.

[0120] In according to an embodiment of the present disclosure, at step S102, the method includes acquiring first clutter estimation results based on the at least two groups of first channel estimation results.

[0121] In according to an embodiment of the present disclosure, at step S103, the method includes performing clutter removal on the at least two groups of first channel estimation results based on the first clutter estimation results to obtain second channel estimation results.

[0122] In 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:

[0123] A1: Performing channel estimation on the echo signals to acquire third channel estimation results, and dividing at least one third channel estimation result obtained at each interval of a preset interval value from among the third channel estimation results into a same group, to acquire at least two groups of first channel estimation results obtained by dividing the channel estimation results.

[0124] A2: Dividing at least one echo signal obtained at each interval of the preset interval value from among the echo signals into a same group to acquire at least two groups of echo signals, and performing channel estimation on the at least two groups of echo signals, to acquire the at least two groups of first channel estimation results obtained by dividing the echo signals.

[0125] Optionally, the first signal may be a signal transmitted by the first node to the second node. Illustratively, the first node may transmit a first signal to the second node, and the second node may transmit a second signal to the first node. In the field of communication and sensing, a first signal and a second signal may be referred to as a sensing signal, and may include a signal transmitted for sensing; accordingly, the first node and the second node may be a communication and sensing node (also referred to as a sensing node). After transmitting a sensing signal, a sensing node can receive echo signals of the sensing signal, , where a positive integer Npis the number of echoes received by the sensing node, and a positive integer Nsis the number of sampling points of a single echo.

[0126] Optionally, when the channel estimation is performed based on the echo signals, the channel estimation may be performed directly on the echo signals, or the echo signals may be grouped first, and then the channel estimation is performed on at least two groups of echo signals obtained after grouping.

[0127] The following is a description of how to obtain at least two groups of first channel estimation results.

[0128] In one possible embodiment, the channel estimation results are grouped to obtain at least two groups of first channel estimation results acquired by dividing the channel estimation results. Specifically, channel estimation is performed on the echo signals to acquire third channel estimation results, at least one third channel estimation result obtained at each interval of a preset interval value from among the third channel estimation results are divided into the same group, to acquire at least two groups of first channel estimation results obtained by dividing channel estimation results.

[0129] The channel estimation can be performed on the acquired Npecho signals to acquire third channel estimation results . It can be understood that the number of echo signals here is the same as the number of third channel estimation results, namely, performing channel estimation on one echo signal can obtain one third channel estimation result. Optionally, one implementation of acquiring the third channel estimation results may be to perform a discrete Fourier transform (DFT) on the echo signals of the first signal, Y, to obtain a time domain representation of the echo signals, Yf, and then perform channel estimation using a least squares (LS) method to obtain the third channel estimation results are reference signals.

[0130] The sensing node can group the third channel estimation results H based on a preset interval value to obtain at least two groups of first channel estimation results after grouping; illustratively, when the interval value is 4, one or more third channel estimation results are obtained at each interval of four third channel estimation results and divided into the same group to obtain at least two groups of first channel estimation results.

[0131] Optionally, the interval value may be the same as the number of groups, e.g. including Npechoes, i.e. including Npthird channel estimation results, Ngis the interval value, the number of third channel estimation results in each group is Nb=Np / Ng, and the number of frequency domain sampling points in each group is Nz=Nb×Ns.At least two groups of first channel estimation results may be acquired by grouping the third channel estimation results.

[0132] Optionally, for Npthird channel estimation results, at least one third channel estimation result can be selected to be grouped in the same group for every Ngchannel estimation results, and at least two groups of first channel estimation results can be obtained after grouping the third channel estimation results H.

[0133] Optionally, one possible grouping aproach is shown in Fig. 7, where the indexes of the third channel estimation results of the received echo signals of the first signal are {1,2,…,Np}, then the index set of the echo signals constituting a first group of the channel estimation results is {1,Ng+1,2Ng+1,…Np-Ng+1}, the index set of the echo signals constituting a second group of the channel estimation results is {2,Ng+2,2Ng+2,…Np-Ng+2}, and so on, the index set of the echo signals constituting a Ng-th group of the channel estimation results is {Ng,2Ng,3Ng,…Np}.

[0134] The value of Ngis a positive integer greater than 1, and is a divisor of Np. It should be noted that the advantage of grouping the channel estimation results is that, by means of the above-mentioned grouping, it can be ensured that all the main frequency-domain characteristics of the clutter contained in each group of channel estimation results, such as the Doppler frequency shift characteristics of the clutter, are preserved, and the frequency-domain characteristics of the clutter in each group of channel estimation results are similar; and by performing feature analysis on a plurality of groups of channel estimation results, it can be achieved that the accuracy of feature analysis of the clutter can be improved. In addition, the value of the interval value Ngdepends on the velocity (Doppler frequency shift) distribution of the clutter in the environment, when the velocity of the clutter is greater or when the high-speed clutter in the velocity distribution of the clutter in the environment occupies a high proportion, to ensure that the Doppler characteristic of the clutter is not lost in each group of channel estimation results (the high-speed clutter can also be reflected in each group of channel estimation results), it is necessary to select one, two or more channel estimation results from the first channel estimation results H of the received echo signal of the first signal at a smaller interval Ngto be divided into the same group, and then the number of channel estimation results in each group increases, and the interval value Ngbecomes smaller. For example, with respect to the sensing node, if the velocity distribution of the clutter in the current detection scene is dominated by zero velocity, the interval value Ngcan be selected to be a larger value; if for the sensing node, if the velocity distribution of the clutter in the current detection scene is mainly at a higher speed, the interval value Ngcan be selected to be a smaller value. The benefit of this is that through flexible adjustment of Ng, it can be ensured that a plurality of groups of channel estimation results can be acquired without losing the clutter velocity information in each group of channel estimation results. The clutter feature extraction based on a plurality of groups of channel estimation results can effectively reduce the impact of noise and improve the accuracy of clutter feature extraction.

[0135] Optionally, when the third channel estimation results are grouped based on the preset interval value, the number of the groups obtained by division is related to the number of the channel estimation results continuously obtained at the interval. In one example, each group of first channel estimation results may include different third channel estimation results obtained at the interval, and there may be consecutive third channel estimation results. In one example, the same third channel estimation results may also be divided into different groups of first channel estimation results, such as when grouping, where there are same third channel estimation results in the first channel estimation results of one group as in the first channel estimation results of another group.

[0136] Exemplification: assuming that there are 10 echo signals (correspondingly, there are 10 third channel estimation results), and the interval value is 5, when a third channel estimation result is acquired at each interval of five third channel estimation results for grouping, it can be obtained that the number of groups is set to be the same as the interval value, and 5 groups of first channel estimation results are obtained; if two or more third channel estimation results obtained at each interval of five third channel estimation results for grouping, and the number of groups is still the same as the interval value, then different groups of channel estimation results include the same third channel estimation results, that is to say, one third channel estimation result will be repeatedly sampled and divided into different groups; if two or more third channel estimation results acquired at each interval of five third channel estimation results for grouping, the configured number of the groups may be related to the number of the two or more third channel estimation results obtained at the interval, and at this time, it may be arranged to group the same third channel estimation results without repeated sampling.

[0137] In one possible embodiment, the echo signals are grouped to acquire at least two groups of first channel estimation results obtained by dividing the echo signals. Specifically, at least two groups of echo signals are acquired by dividing at least one echo signal obtained at each interval of the interval value from among the echo signals into the same group, and channel estimation is performed on at least two groups of echo signals to obtain at least two groups of first channel estimation results obtained by dividing the echo signals.

[0138] The sensing node can group the acquired Npecho signals based on a preset interval value to obtain at least two groups of echo signals after grouping; and for example, when the interval value is 5, one or more echo signals can be acquired at each interval of 5 echo signals and divided into the same group to obtain at least two groups of echo signals.

[0139] Optionally, the interval value may be the same as the number of groups, e.g. including Npechoes, Ngis the interval value, the number of echo signals in each group is Nb=Np / Ng, and the number of frequency domain sampling points in each group being Nz=Nb×Ns.

[0140] Optionally, given a possible grouping approach, the indexes of the received echo signals of the first signal are {1,2,…,Np}, then the index set of the echo signals constituting the first group is {1,Ng+1,2Ng+1,…Np-Ng+1}, the index set of the echo signals constituting the second group is {2,Ng+2,2Ng+2,…Np-Ng+2}, and so on, the index set of the echo signals constituting the Ng-th group is {Ng,2Ng,3Ng,…Np}.

[0141] The value of Ngis a positive integer greater than 1, and is a divisor of Np. It should be noted that the advantage of grouping the echo signals is that, by means of the above-mentioned grouping, it can be ensured that all the main frequency-domain characteristics of the clutter contained in each group of echo signals, such as the Doppler frequency shift characteristics of the clutter, are preserved, and the frequency-domain characteristics of the clutter in each group of echo signals are similar; and by performing channel estimation on a plurality of groups of echo signals and then performing feature analysis, the accuracy of feature analysis of the clutter can be improved. In addition, the value of the interval value Ngdepends on the velocity (Doppler frequency shift) distribution of the clutter in the environment, when the velocity of the clutter is greater or when the high-speed clutter in the velocity distribution of the clutter in the environment occupies a high proportion, to ensure that the Doppler characteristic of the clutter is not lost in each group of echo signals (the high-speed clutter can also be reflected in each group of echo signals), it is necessary to select one, two or more echo signals from the received echo signals of the first signal to be divided into the same group at a smaller interval Ng, then the number of echo signals in each group increases and the interval value Ngdecreases. For example, concerning the sensing node, if the velocity distribution of the clutter in the current detection scene is dominated by zero velocity, the interval value Ngcan be selected to be a larger value; if for the sensing node, if the velocity distribution of the clutter in the current detection scene is mainly at a higher speed, the interval value Ngcan be selected at a smaller value. The benefit of this is that through flexible adjustment of Ng, it can be ensured that a plurality of groups of echo signals can be obtained without loss of clutter velocity information in each group of echo signals. After channel estimation based on a plurality of groups of echo signals, clutter feature extraction can effectively reduce the impact of noise and improve the accuracy of clutter feature extraction.

[0142] Optionally, one implementation for acquiring at least two groups of first channel estimation results may be to perform a DFT on each group of echo signals, Y, to obtain a time domain representation Yfof the echo signals, and then to perform channel estimation using an LS method to obtain at least two groups of channel estimation results.

[0143] Optionally, when the echo signals are grouped based on a preset interval value, the number of groups obtained by the division is related to the number of echo signals continuously obtained at the interval. In one example, different echo signals obtained at the interval may be included in each group of echo signals, and there may be consecutive echo signals. In one example, the same echo signals may also be divided into different groups of echo signals, e.g., when grouped, the echo signals of one group have the same echo signals as the echo signals of another group. Exemplification: assuming that there are 10 echo signals, and the interval value is 5, when acquiring one echo signal at each interval of five interval echo signals for grouping, it can be obtained to set that the grouping number is the same as the interval value to obtain 5 groups of echo signals; if two or more echo signals are acquired at each interval of five echo signals for grouping, and the number of groups is still the same as the interval value, then different groups of echo signals include the same echo signal, that is to say, an echo signal will be repeatedly sampled and divided into different groups; if two or more echo signals are acquired at each interval of five echo signals for grouping, the configured number of groups can be related to the number of two or more echo signals obtained at the interval, and at this time, it can be arranged to group the same echo signals without repeated sampling.

[0144] Optionally, before grouping the third channel estimation results or the echo signals, operation of determining an interval value based on a Doppler frequency distribution of non-target objects in a preset detection scene.

[0145] The target object in the preset detection scene includes an object to be detected in the detection scene. Illustratively, assuming that the current task is to detect an unmanned aerial vehicle in the sky, the target object in the detection scene at this time is the unmanned aerial vehicle, and the objects other than the unmanned aerial vehicle are non-target objects (clutter), such as a cloud, a bird, etc. and an interval value can be determined based on a Doppler frequency distribution preset for the non-target object. Illustratively, assuming that the current task is to detect a ship in the sea, then in this detection scenario the ship is the target object and the objects other than the ship are non-target objects (clutter), such as sea water, fish, etc. and an interval value may be determined based on the Doppler frequency distribution preset for the non-target objects.

[0146] Optionally, the sensing node may perform clutter feature analysis based on at least two groups of first channel estimation results G to acquire first clutter estimation results. The method of clutter feature analysis may use eigenvalue decomposition (EVD) or singular value decomposition (SVD). One possible implementation is to perform an SVD on at least two groups of first channel estimation results G, , where U and V are orthogonal matrices and Σ is a diagonal matrix containing singular values. Based on the results of SVD, the main singular vectors in the matrix V (or U) corresponding to the first L, L≤Ng, largest singular values in Σ is selected to form the matrix for estimating the clutter subspace, and the matrix C composed of the main singular vectors can capture the main features of the clutter echo. When L<<Ng, the complexity of clutter reconstruction based on the matrix C composed of the main singular vectors can be greatly reduced, and the value of L can be 2 to 4 in a common outdoor scene. It should be noted that the process of clutter feature analysis can be real-time or non-real-time depending on the processing capability of the sensing node. The real-time clutter feature analysis can be that after receiving the Np-th echo signal, the sensing node can complete clutter feature analysis before obtaining the next Npecho signals, and extract the clutter feature; the non-real time clutter feature analysis may be that after receiving the kNp-th echo signal, the sensing node completes the clutter feature analysis based on the first previous Npechoes to extract the clutter feature; the value of k is dependent on the data processing capability of the sensing node, and the greater the k value, the weaker the data processing capability of the sensing node is. The benefit of real-time clutter feature analysis of the sensing node is that the extracted clutter features can reflect the current environmental clutter in real-time, and the sensing performance can be significantly improved after the environmental clutter removal. When the sensing node can perform non-real-time clutter feature analysis, the extracted clutter feature can be used for subsequent real-time clutter reconstruction, and clutter removal can be performed in the received echo signals.

[0147] Optionally, the first clutter estimation results obtained from the clutter feature analysis includes a matrix for clutter reconstruction (the process of obtaining the matrix may be considered as a first clutter estimation). The sensing node may obtain a matrix for clutter reconstruction (first clutter estimation results) based on a matrix C composed of main singular vectors, and the matrix may be used for real-time clutter reconstruction and clutter removal. One possible implementation for obtaining a clutter reconstruction matrix is to acquire based on a matrix C, the matrix P1may be stored for later real-time clutter estimation. Alternatively, another implementation for obtaining a clutter reconstruction matrix is to acquire based on a matrix C, where the matrices P2and C can be saved for later real-time clutter estimation, which has the advantage of reducing the computational complexity of the matrix multiplication. It is to be noted that when the background environment changes, the matrices P1or P2and C may no longer reflect the clutter after the environment change, and therefore it is necessary to perform the clutter estimation method provided by the above-mentioned embodiment again to obtain a new matrices P1or P2and C for reflecting the clutter after the environment change.

[0148] Optionally, the sensing node may reconstruct first clutter estimation results (also referred to as first clutter signals) based on matrices (matrices P1or P2and C) used for clutter reconstruction and at least two groups of first channel estimation results G. One possible method for reconstructing the clutter estimation results includes obtaining reconstructed first clutter signals based on the reconstructed matrix P1and at least two groups of first channel estimation results G. Alternatively, one possible method for reconstructing the clutter signals includes obtaining reconstructed clutter signals based on the matrices P2and C for reconstruction, and at least two groups of first channel estimation results G.

[0149] Optionally, when the sensing node performs clutter removal on at least two groups of first channel estimation results, reconstructed clutter signals can be removed from at least two groups of first channel estimation results G (first clutter removal) to obtain a channel estimation results Grafter the first clutter removal. Specifically, the method of removal may be . The sensing node rearranges elements in the channel estimation results Grafter the first clutter removal to obtain the channel estimation results (also referred to as second channel estimation results) after the first clutter removal. One possible arrangement is shown in Fig. 9, where each group of elements in the first column in Gr(each group of elements contains Ns sample points) is arranged in a column of Hr1by indexes {1,Ng+1,2Ng+1,…Np-Ng+1}, each group of elements in the second column in Gr(each group of elements contains Ns sample points) is arranged in a column of Hr1by indexes {2,Ng+2,2Ng+2,…Np-Ng+2}, and so on, and each group of elements in the Ng-th column in Gr(each group of elements contains Ns sample points) is arranged in a column of Hr1by indexes {Ng,2Ng,3Ng,…Np}, finally forming second channel estimation results Hr1.

[0150] Optionally, the first clutter estimation may be a non-real-time clutter estimation.

[0151] An embodiment of the present disclosure can process a group of echo signals acquired cumulatively, and when channel estimation is performed to obtain at least two groups of first channel estimation results, third channel estimation results or echo signals can be grouped based on a preset interval value to effectively reduce the computational complexity and improve the processing efficiency by grouping; in addition, clutter feature extraction can be performed based on a plurality of groups of channel estimation results, which can effectively reduce the impact of noise and improve the accuracy of clutter feature extraction, to effectively improve the detection capability of the sensed target object.

[0152] In a possible embodiment, the provided method further includes S104: if it is determined to perform clutter estimation based on the second channel estimation results, performing at least one of the following operations 1 to 2:

[0153] Operation 1: performing clutter estimation based on at least one of the first signal and the third channel estimation results to obtain second clutter estimation results, and performing clutter removal on the third channel estimation results based on the second clutter estimation results to obtain fourth channel estimation results, to perform target detection based on at least one of the second channel estimation results and the fourth channel estimation results.

[0154] The communication and sensing node may determine whether a real-time clutter estimation (a second clutter estimation) needs to be performed based on the second channel estimation results; illustratively, 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 results, and the obtained second clutter estimation results may be used for performing clutter removal.

[0155] Optionally, if the communication and sensing node determines that the second clutter estimation needs to be performed, the communication and sensing node performs the second clutter estimation based on the first signal and / or the third channel estimation results to obtain the second clutter estimation results, and performs clutter removal on the third channel estimation results based on the second clutter estimation results to obtain fourth channel estimation results. On the other hand, if the communication and sensing node determines that the second clutter estimation is not needed, the communication and sensing node does not perform the clutter estimation and the clutter removal. Then, based on the determination result, the communication and sensing node may perform target detection based on the second channel estimation results and / or the fourth channel estimation results.

[0156] Operation 2: performing clutter estimation based on at least one of the first signal and the at least two groups of first channel estimation results obtained by dividing the echo signals to obtain third clutter estimation results, and performing clutter removal on the at least two groups of first channel estimation results obtained by dividing the echo signals based on the third clutter estimation results to obtain fifth channel estimation results, to perform target detection based on at least one of the second channel estimation results and the fifth channel estimation results.

[0157] The communication and sensing node can determine whether a real-time clutter estimation (a third clutter estimation) needs to be performed based on the second channel estimation results; illustratively, the third clutter estimation can be a real-time clutter estimation performed by the communication and sensing node based on at least one of a frequency domain signal of a received first signal and at least two groups of first channel estimation results obtained by dividing the echo signals, and the obtained third clutter estimation results can be used for performing clutter removal.

[0158] Optionally, if the communication and sensing node determines that a third clutter estimation needs to be performed, the communication and sensing node performs the third clutter estimation based on the first signal and / or at least two groups of first channel estimation results obtained by dividing the echo signals to obtain third clutter estimation results, and performs clutter removal on at least two groups of first channel estimation results obtained by dividing the echo signals based on the third clutter estimation results to obtain fifth channel estimation results. On the other hand, if the communication and sensing node determines that the third clutter estimation is not needed, the communication and sensing node does not perform the clutter estimation and the clutter removal. Then, based on the determination result, the communication and sensing node may perform target detection based on the second channel estimation results and / or the fifth channel estimation results.

[0159] In a possible embodiment, the operation of performing clutter estimation based on at least one of the first signal and the third channel estimation results to obtain second clutter estimation results, and performing clutter removal on the third channel estimation results based on the second clutter estimation results includes:

[0160] constructing a first matrix of a clutter subspace based on at least one of a frequency domain signal of the first signal and the third channel estimation results;

[0161] performing signal reconstruction based on the first matrix and the third channel estimation results to acquire reconstructed second clutter estimation results; and

[0162] performing clutter removal on the third channel estimation results based on the second clutter estimation results to obtain the fourth channel estimation results.

[0163] Optionally, the sensing node obtains a projection matrix of the clutter subspace (also referred to as a first matrix, the process of obtaining the first matrix may be considered as performing a second clutter estimation, a real-time 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, the sensing signal may be a symbol based on OFDM modulation. Specifically, the constructed clutter subspace can be expressed as , where is the reference signal corresponding to the k -th sub-carrier in the frequency domain signal of the i -th sensing signal, Npis the number of sensing signals, and Nsis the number of sub-carriers of the frequency domain signal of the sensing signals. Based on the clutter subspace, the communication and sensing node can obtain the projection matrix of the clutter subspace , and when the number of sub-carriers is Ns, the communication and sensing node can obtain the projection matrix of Nsclutter subspaces. Optionally, it is also possible to construct a clutter subspace based on the third channel estimation results based on the same method and obtain a projection matrix based on the clutter subspace. In a possible embodiment, one possible method for the sensing node to obtain the clutter subspace in the present disclosure may further be to construct the clutter subspace based on the frequency domain signal of the first signal and the third channel estimation results, and to obtain the first matrix based on the clutter subspace.

[0164] Optionally, the sensing node reconstructs second clutter signals (also referred to as second clutter estimation results) based on the projection matrix of the clutter subspace. The reconstruction method may be that the sensing node multiplies the third channel estimation results obtained by performing channel estimation on the echo signals of the first signal with a projection matrix of a clutter subspace to obtain second clutter signals. The third channel estimation results are is a channel estimation result corresponding to a single sensing signal; the sensing signal can be a symbol modulated based on an OFDM symbol, and zi,i=1,...,Nsis a frequency domain estimation result corresponding to a single sub-carrier of the frequency domain sensing signal. H may be the third channel estimation results in the above-mentioned embodiment, and an acquisition example of the channel estimation result will not be described here. The sensing node obtains the second clutter signals based on a projection matrix of Nsclutter subspaces, where is a frequency domain estimation result corresponding to a single sub-carrier of the frequency domain sensing signal.

[0165] Optionally, the sensing node removes the reconstructed second clutter signals Hc2from the third channel estimation results H (second clutter removal) to acquire fourth channel estimation results Hr2(also referred to as channel estimation results after the second clutter removal). Specifically, the method of removal may be Hr2=H-Hc2.

[0166] In a possible embodiment, the operation of performing clutter estimation based on at least one of the first signal and the at least two groups of first channel estimation results obtained by dividing the echo signals to obtain third clutter estimation results, and performing clutter removal on the at least two groups of first channel estimation results obtained by dividing the echo signals based on the third clutter estimation results to obtain fifth channel estimation results includes:

[0167] constructing a second matrix of the clutter subspace based on at least one of the frequency domain signal of the first signal and the at least two groups of first channel estimation results obtained by dividing the echo signals;

[0168] performing signal reconstruction based on the second matrix and the at least two groups of first channel estimation results obtained by dividing the echo signals to acquire reconstructed third clutter estimation results; and

[0169] performing, based on the third clutter estimation results, clutter removal on the at least two groups of first channel estimation results obtained by dividing the echo signals, to obtain the fifth channel estimation results.

[0170] Optionally, the manner of constructing the second matrix (projection matrix) of the clutter subspace and the manner of performing the signal reconstruction to obtain the third clutter estimation results may be performed with reference to the manner of obtaining the first matrix and the second clutter estimation results in the embodiments described above, and will not be described in detail herein in the present disclosure.

[0171] Optionally, after obtaining the fourth channel estimation results or the fifth channel estimation results, the following steps are further included:

[0172] determining whether the target detection based on the fourth channel estimation results or the fifth channel estimation results satisfies a first condition;

[0173] if the first condition is satisfied, constructing a third matrix of the clutter subspace based on results of the target detection;

[0174] performing signal reconstruction based on the third matrix and the third channel estimation results to acquire reconstructed fourth clutter estimation results; or performing signal reconstruction based on the third matrix and the at least two groups of first channel estimation results obtained by dividing the echo signals, to obtain fifth clutter estimation results; and

[0175] performing clutter removal on the third channel estimation results based on the fourth clutter estimation results to obtain sixth channel estimation results; or performing clutter removal on at least two groups of first channel estimation results obtained by dividing the echo signals based on the fifth clutter estimation results, to obtain seventh channel estimation results.

[0176] Optionally, the manner of constructing the third matrix (projection matrix) of the clutter subspace may be performed with reference to the manner of constructing the first matrix of the clutter subspace in the above-described embodiments, and will not be described in detail herein in the present disclosure.

[0177] In one example, the sensing node may apply a target detection algorithm to the fourth channel estimation results Hr2or the fifth channel estimation results to detect and estimate parameters of the desired target object. Specifically, the sensing node may obtain a signal in the delay domain by performing an inverse discrete Fourier transform (IDFT) on Hr2column by column, obtain a signal in the Doppler domain by performing a DFT row by row, and detect a distance or velocity (Doppler frequency) of a single or a plurality of target objects by fixed threshold detection; the distance may be obtained by multiplying the delay by the speed of light and then being divided by two, and the velocity may be obtained by multiplying the Doppler frequency by the wavelength of the sensing signal and then being divided by two.

[0178] Optionally, the sensing node may determine whether there is a target object satisfying the first condition based on the result of the target detection or in the process of the target detection, if yes, repeat the above-mentioned step of determining whether the first condition is satisfied, and if not, the process is ended.

[0179] Optionally, the first condition includes at least one of the following:

[0180] (1) It is detected that the power of the fourth channel estimation results or the fifth channel estimation results of a target object is greater than the power of noise floor (greater than 0), and a detected Doppler frequency of a target object is not equal to 0;

[0181] Determination is made as to whether the power of the fourth channel estimation results or the fifth channel estimation results of a target object satisfies 0<p1<pi, and Doppler fi>0; Ntis the number of sensing targets detected by a communication and sensing node, p1(unit: watt) is a fixed threshold. Specifically, one possible value of p1is the power of noise floor, and the value of the power of noise floor can be a theoretical value or an actual measurement. The advantage of setting the condition in this way is that when the power of the fourth channel estimation results or the fifth channel estimation results of a real target object whose Doppler is not zero is greater than p1, a false target may be generated in the same distance corresponding thereto, and the condition can quickly screen out a real target object for which a false target may occur, and reduce the influence on target detection due to clutter removal.

[0182] (2) It is detected that the power of the fourth channel estimation results or the fifth channel estimation results of the target object is greater than the power of noise floor (greater than 0), and the detected Doppler frequency of the target object is an integer multiple of non-zero Doppler resolution.

[0183] Determination is made as to whether the power of the fourth channel estimation results or the fifth channel estimation results of the target object satisfies 0<p1<pi, and Doppler fi=kfΔ,k=1,2,...,Nt; Ntis the number of sensing targets detected by a communication and sensing node, p1(unit: watt) is a fixed threshold, fΔ(units: hertz) is the Doppler resolution. Specifically, one possible value of p1is the power of noise floor, and the value of the power of noise floor can be a theoretical value or an actual measurement. The advantage of setting the condition in this way is that when the Doppler of a real target object with a Doppler different from zero is an integer multiple of the Doppler resolution, the power of the corresponding fourth channel estimation results or the fifth channel estimation results of a false target in the same distance will be higher, and the condition can effectively screen out a real target object with a higher power of the corresponding fourth channel estimation results or the fifth channel estimation results of a false target, reduce the computational complexity of a clutter subspace projection matrix and reduce the influence on target detection due to clutter removal.

[0184] (3) It is detected that the power of the fourth channel estimation results or the fifth channel estimation results of the target object corresponding to at least one of the preset distance and the preset angle is greater than the power of noise floor, and the detected Doppler frequency of the target object is not equal to 0.

[0185] The consideration of at least one of a distance and an angle is added in the condition (3) with respect to the condition (1) in the first condition. In some specific scenarios, it may be necessary to consider the situation within a certain distance or under a certain angle, and at this time, to effectively reduce the computational complexity and improve the efficiency of target detection, the consideration may be made according to the fourth channel estimation results or the fifth channel estimation results of the target object corresponding to at least one of a preset distance and a preset angle for the requirements of the current detection task.

[0186] (4) It is detected that the power of the fourth channel estimation results or the fifth channel estimation results of the target object corresponding to at least one of the preset distance and the preset angle is greater than the power of noise floor, and detected Doppler frequency of the target object is an integer multiple of non-zero Doppler resolution.

[0187] The consideration of at least one of a distance and an angle is added in the condition (4) with respect to the condition (2) in the first condition. In some specific scenarios, it may be necessary to consider the situation within a certain distance or under a certain angle, and at this time, to effectively reduce the computational complexity and improve the efficiency of target detection, the consideration may be made according to the fourth channel estimation results or the fifth channel estimation results of the target object corresponding to at least one of a preset distance and a preset angle for the requirements of the current detection task.

[0188] It should be noted that when the power of the fourth channel estimation results or the fifth channel estimation results of a target object with a Doppler frequency different from zero is high, clutter removal performed after real-time clutter estimation may result in the occurrence of a false target, resulting in a high false alarm probability. Specifically, the Doppler frequency of the false target is zero, which is the same distance as that of the sensed target object with a detected non-zero Doppler frequency. The advantage of using the first condition to select a detection target that satisfies the condition is that a sensed target object that causes a false target can be simply screened out to suppress the effects of the false target that it causes.

[0189] In one example, the sensing node acquires a new clutter subspace projection matrix based on the target detection results and then performs clutter signal reconstruction. Specifically, the sensing node can construct a new clutter subspace based on the clutter subspace ; is the reference signal corresponding to the k -th sub-carrier in the frequency domain signal of the i -th sensing signal, Npis the number of sensing signals, and Nsis the number of sub-carriers of the frequency domain signals of the sensing signals, where , are the Doppler frequencies corresponding to the Nvdetected target objects with non-zero Doppler in S905, Tsis the signal duration of a sensing signal, and Npis the number of sensing signals. Based on the new clutter subspace, the communication and sensing node can obtain a projection matrix

[0190] of the new clutter subspace, and when the number of sub-carriers is Ns, the communication and sensing node can obtain Nsprojection matrices of the new clutter subspace. It should be noted that the advantage of using the new clutter subspace projection to construct the clutter signals is that the false target generated by the target object with high Doppler frequency on the equidistant zero Doppler frequency can be effectively suppressed and the false alarm probability can be reduced.

[0191] In a possible embodiment, the operation of determining to perform clutter estimation based on the second channel estimation results includes:

[0192] determining whether the second channel estimation results satisfy a preset second condition;

[0193] determining to perform clutter estimation if the second channel estimation results satisfy the second condition; and

[0194] performing target detection based on the second channel estimation results if the second channel estimation results do not satisfy the second condition.

[0195] Optionally, the sensing node may determine whether the second condition is satisfied based on the second channel estimation results Hr1, perform real-time clutter estimation and clutter removal when the second condition is satisfied, and perform target object detection based on the second channel estimation results when the second condition is not satisfied.

[0196] Optionally, the sensing node may apply a target detection algorithm to the second channel estimation results Hr1to detect and estimate parameters of the desired target object. Specifically, the sensing node may obtain a signal in the delay domain by performing an IDFT on Hr1column by column, obtain a signal in the Doppler domain by performing a DFT row by row, and detect a distance or velocity (Doppler frequency) of a single or a plurality of target objects by fixed threshold detection; the distance may be obtained by multiplying the delay by the speed of light and then being divided by two, and the velocity may be obtained by multiplying the Doppler frequency by the wavelength of the sensing signal and then being divided by two.

[0197] Optionally, the second condition includes at least one of the following:

[0198] (1) The power of noise floor of the second channel estimation results is greater than or equal to a preset threshold value related to the detected distance of the target object and / or the RCS of the target object.

[0199] The power of noise floor (unit: watt) of the second channel estimation results Hr1is greater than p2+Δ; the value of p2(units: watt) may be the power of noise floor of the channel estimation results after performing the first clutter estimation and removal based on the channel estimation results, Δ (unit: watt) is a positive number greater than zero, the value of which depends on the target object perceived in the environment. Specifically, Δ can take a larger value when the target object is close and / or its RCS is higher; Δ may take a value of 0 or less when the target object is far away and / or its RCS is small. When the power of noise floor of Hr1is greater than p2+Δ, it can reflect that the clutter estimation results reconstructed based on the clutter reconstruction matrix cannot reflect the clutter in the current environment, which results in that the residual clutter components after the clutter removal of the sensing node will affect the detection of the actual target object.

[0200] (2) The power of the channel estimation results corresponding to the zero Doppler frequency in the second channel estimation results is greater than or equal to a preset threshold value.

[0201] A zero Doppler frequency indicates a stationary target object, i.e. a Doppler frequency with zero velocity.

[0202] (2.1) The average power of the channel estimation results corresponding to the zero Doppler component in the second channel estimation results is greater than or equal to a preset threshold value related to the detected distance of the target object and / or the RCS of the target object.

[0203] The average power (unit: watt) of channel estimation results hr1corresponding to zero Doppler component after clutter removal is greater than p3+Δ, where the value of p3(units: watt) may be the average power of the estimation results of the zero-Doppler component after clutter estimation and removal based on the channel estimation results, Δ (unit: watt) is a positive number greater than zero, the value of which depends on the target object perceived in the environment. Specifically, Δ may take a larger value when the target object is close and / or its RCS is higher; Δ may take a value of 0 or less when the target object is far away and / or its RCS is small. When the average power of hr1is greater than p3+Δ, it can reflect that the clutter estimation result reconstructed based on the clutter reconstruction matrix cannot reflect the zero-Doppler clutter component (static) in the current environment, which results in that the residual zero-Doppler clutter component after the clutter removal of the sensing node will affect the detection of the static real target object.

[0204] (2.2) The highest power of the channel estimation results corresponding to the zero Doppler component in the second channel estimation results is greater than or equal to a preset threshold value related to the detected distance of the target object and / or the RCS of the target object.

[0205] The highest power of the channel estimation results hr1corresponding to the zero Doppler component after clutter removal is greater than p4+Δ, where p4(unit: watt) may be the highest power of the zero-Doppler component estimation results after clutter estimation and removal based on the channel estimation results, Δ (unit: watt) is a positive number greater than zero, the value of which depends on the target object perceived in the environment. Specifically, Δ may take a larger value when the target object is close and / or its RCS is higher; Δ may take a value of 0 or less when the target object is far away and / or its RCS is small. By deciding whether the highest power of hr1is greater than p4+Δ or not, it can be easily and quickly decided whether the clutter estimation results reconstructed based on the clutter reconstruction matrix can also reflect the zero-Doppler clutter component (static state) in the current environment, resulting in that the residual zero-Doppler clutter component after the clutter removal of the sensing node will affect the detection of the static actual target object.

[0206] (3) The power of noise floor corresponding to at least one of a preset distance and a preset angle in the second channel estimation results is greater than or equal to the preset threshold value.

[0207] The consideration of at least one of a distance and an angle is added in the condition (3) with respect to the condition (1) in the second condition, and in some detection scenarios, it may be necessary to specifically consider the situation under certain distances and angles, and to effectively reduce the computational complexity and improve the target detection efficiency, a low-noise function corresponding to at least one of a preset distance and a preset angle in the second channel estimation results may be considered for the current detection requirements.

[0208] (4) The power of channel estimation results corresponding to a zero Doppler frequency corresponding to at least one of a preset distance and a preset angle in the second channel estimation results is greater than or equal to the preset threshold value.

[0209] Relative to condition (2) in the second condition, the consideration of at least one of a distance and an angle is added in condition (4). In some specific scenarios, it may be necessary to consider the situation within a certain distance or under a certain angle, and at this time, to effectively reduce the computational complexity and improve the efficiency of target detection, channel estimation results corresponding to a zero Doppler frequency according to at least one of a preset distance and a preset angle may be considered with respect to the requirements of the current detection task.

[0210] The method provided by the present disclosure is described below in connection with some optional embodiments (the first, second, third, etc. order in the following embodiments is independent of the expressions in the above embodiments, i.e. the first, second, etc. order expressions in the following embodiments one to five are only functional in the corresponding embodiments).

[0211] Embodiment 1

[0212] The embodiment provides a method for adaptive clutter estimation and removal, as shown in Fig. 5, and the specific steps are as follows.

[0213] In accordance with an embodiment of the present disclosure, at step S401, the communication and sensing node performs first clutter estimation, and then based on the first clutter estimation results, the communication and sensing node performs first clutter removal on the echo signals of the transmitted first signal. The first clutter estimation can be the above-mentioned non-real-time clutter estimation, and the clutter estimation result cannot be obtained in real time, and can only be obtained after a required certain processing time (as in Embodiment 2), and clutter removal cannot be performed on the current received echo signals based on the first clutter estimation results. After acquiring the first clutter estimation results, based on the first clutter estimation results, the communication and sensing node can perform real-time clutter reconstruction, and perform first clutter removal (as in Embodiment 3) on the echo signals of the transmitted first signal (such as channel estimation results after first clutter removal); the first signal can be a signal transmitted by the communication and sensing node for sensing.

[0214] In accordance with an embodiment of the present disclosure, at step S402, the communication and sensing node determines whether a second clutter estimation needs to be performed based on the echo signals after the first clutter removal (as in Embodiment 5); specifically, the second clutter estimation can be a real-time clutter estimation which can be performed based on the received echo signals by the communication and sensing node, and the obtained second clutter estimation results can be used for performing clutter removal on the currently received echo signals (such as channel estimation results corresponding to the echo signals) (as in Embodiment 4). If the communication and sensing node determines that a second clutter estimation needs to be performed, the communication and sensing node performs the second clutter estimation to obtain second clutter estimation results, and performing second clutter removal on the echo signals based on the second clutter estimation results. On the other hand, if the communication and sensing node determines that the second clutter estimation is not needed, the communication and sensing node does not perform the second clutter estimation and the second clutter removal.

[0215] In accordance with an embodiment of the present disclosure, at step S403, the communication and sensing node performs target object detection based on the echo signals after the first and / or second clutter removal.

[0216] Embodiment 2

[0217] Fig. 6 illustrates a flow diagram of a method for first clutter estimation according to an embodiment of the present disclosure.

[0218] According to Embodiment 1, a method for a communication and sensing node to perform first clutter estimation is shown in Fig. 6:

[0219] In accordance with an embodiment of the present disclosure, at step S501, a sensing node sends a sensing signal and receives echo signals , where a positive integer Npis the number of echoes received by the sensing node, and a positive integer Nsis the number of sampling points of a single echo.

[0220] In accordance with an embodiment of the present disclosure, at step S502, the sensing node performs channel estimation on the echo signals to obtain channel estimation results . Specifically, one implementation of obtaining channel estimation results is to perform a DFT on an echo signals Y to obtain a time domain expression Yfof the echo signals, and then perform channel estimation using an the LS method to obtain is the reference signal.

[0221] In accordance with an embodiment of the present disclosure, at step S503, the sensing node groups the channel estimation results H to obtain Nggroups of channel estimation results; the number of channel estimation results in each group is Nb=Np / Ng, and the number of frequency domain sampling points in each group is Nz=Nb×Ns. That is, for Npchannel estimation results, selecting one channel estimation result every Ngchannel estimation results to be grouped in the same group, and grouping the channel estimation results H can obtain the grouped channel estimation results . Specifically, one possible grouping approach is as shown in Fig. 7, if the indexes of the channel estimation results of the received echo signals are {1,2,…,Np}, then the index set of the echo signals constituting the first group of channel estimation results is {1,Ng+1,2Ng+1,…Np-Ng+1}, the index set of the echo signals constituting the second group of channel estimation results is {2,Ng+2,2Ng+2,…Np-Ng+2}, and so on, the index set of the echo signals constituting the Ng-th group of channel estimation results is {Ng,2Ng,3Ng,…Np}. The value of Ngis a positive integer greater than 1, and is a divisor of Np. It should be noted that the advantage of grouping the channel estimation results is that, by means of the above-mentioned grouping, it can be ensured that all the main frequency-domain characteristics of the clutter contained in each group of channel estimation results, such as the Doppler frequency shift characteristics of the clutter, are preserved, and the frequency-domain characteristics of the clutter in each group of channel estimation results are similar; and by performing feature analysis on a plurality of groups of channel estimation results, it can be achieved that the accuracy of feature analysis of the clutter can be improved. In addition, the value of the number of groups Ngdepends on the distribution of the velocity (Doppler frequency shift) of the clutter in the environment; when the velocity of the clutter is greater or when the high-speed clutter occupies a high proportion in the distribution of the velocity of the clutter in the environment, to ensure that the Doppler characteristics of the clutter are not lost in each group of channel estimation results (the high-speed clutter can also be reflected in each group of channel estimation results), it is necessary to select one channel estimation result from the channel estimation results H of the received echo signals to be divided into the same group at a smaller interval Ng, and then the number of channel estimation results in each group increases and the number of groups Ngdecreases. For example, with respect to the sensing node, if the velocity distribution of the clutter in the current detection scene is mainly zero velocity, the number of groups Ngcan be selected to be a larger value; if for the sensing node, if the velocity distribution of clutter in the current detection scene is mainly at a higher speed, the number of groups Ngcan be selected to be a smaller value. The benefit of this is that through flexible adjustment of Ng, it can ensure that a plurality of groups of channel estimation results can be obtained without loss of clutter velocity information in each group of channel estimation results, and clutter feature extraction based on a plurality of groups of channel estimation results can effectively reduce the impact of noise and improve the accuracy of clutter feature extraction.

[0222] In accordance with an embodiment of the present disclosure, at step S504, the sensing node performs clutter feature analysis based on the grouped channel estimation results G, and the method for performing the clutter feature analysis may be to use EVD or SVD. Specifically, one possible implementation is to perform an SVD on the grouped channel estimation results G, , where U and V are orthogonal matrices, and Σ is a diagonal matrix containing singular values. Based on the results of SVD, the main singular vectors in the matrix V (or U) corresponding to the first L, L≤Ng, largest singular values in Σ is selected to form the matrix for estimating the clutter subspace, and the matrix C composed of the main singular vectors can capture the main features of the clutter echo. When L<<Ng, the complexity of clutter reconstruction based on the matrix C composed of the main singular vectors can be greatly reduced, and the value of L can be 2 to 4 in a common outdoor scene. It should be noted that the process of clutter feature analysis can be real-time or non-real-time according to the processing capability of the sensing node. The real-time clutter feature analysis can be that after the sensing node receives the Np-th echo signal, the sensing node can complete clutter feature analysis before acquiring the next Npecho signals, and extract the clutter feature; the non-real time clutter feature analysis may be that after the sensing node receives the kNp-th echo signal, the sensing node completes the clutter feature analysis based on the first previous Npechoes to extract the clutter feature; the value of k is dependent on the data processing capability of the sensing node, and the greater the k value, r the weaker the data processing capability of the sensing node is. The benefit of real-time clutter feature analysis of the sensing node is that the extracted clutter features can reflect the current environmental clutter in real-time, and the sensing performance can be significantly improved after the environmental clutter removal. When the sensing node can only perform non-real-time clutter feature analysis, the extracted clutter feature can be used for subsequent real-time clutter reconstruction, and clutter removal can be performed in the received echo signals.

[0223] In accordance with an embodiment of the present disclosure, at step S505, the sensing node obtains a matrix (first clutter estimation) for clutter reconstruction based on a matrix C composed of main singular vectors, which can be used for real-time clutter reconstruction and clutter removal. One possible implementation for obtaining a clutter reconstruction matrix is to acquire based on a matrix C, the matrix P1may be stored for later real-time clutter estimation. Alternatively, another implementation for obtaining a clutter reconstruction matrix is to acquire based on a matrix C, where the matrices P2and C can be saved for later real-time clutter estimation, which has the advantage of reducing the computational complexity of the matrix multiplication. The specific process of performing clutter reconstruction based on the clutter reconstruction matrix is described in detail in Embodiment 3. It is to be noted that when the background environment changes, the matrices P1or P2and C may no longer reflect the clutter after the environment change, and therefore new matrices P1, or P2and C need to be acquired again according to steps S501 to S505 for reflecting the clutter after the environment change.

[0224] Embodiment 3

[0225] According to Embodiment 1, a method for a communication and sensing node to perform a first clutter removal is shown in Fig. 8:

[0226] S701: A sensing node sends a sensing signal and receives echo signals , where a positive integer Npis the number of echoes received by the sensing node, and a positive integer Nsis the number of sampling points of a single echo.

[0227] S702: The sensing node performs channel estimation on the echo signals to obtain channel estimation results . Specifically, one implementation of obtaining channel estimation results is to perform a DFT on echo signals Y to obtain a time domain expression Yfof the echo signals, and then perform channel estimation using an LS method to obtain is the reference signal.

[0228] S703: The sensing node group the channel estimation results H to obtain Nggroups of channel estimation results, the number of echoes in each group is Nb=Np / Ng, and the number of frequency domain sampling points in each group is Nz=Nb×Ns. Then, grouped channel estimation results can be obtained after grouping the channel estimation results H; specifically, one possible grouping method is as shown in Fig. 7, the indexes of the channel estimation results of the received echo signals are {1,2,…,Np}, then the index set of the echo signals constituting the first group of channel estimation results is {1,Ng+1,2Ng+1,…Np-Ng+1}, the index set of the echo signals constituting the second group of channel estimation results is {2,Ng+2,2Ng+2,…Np-Ng+2}, and so on, the index set of the echo signals constituting the Ng-th group of channel estimation results is {Ng,2Ng,3Ng,…Np}.

[0229] S704: The sensing node reconstructs clutter signals based on the matrix for clutter reconstruction and the grouped channel estimation results G. The acquisition of matrices P1or P2and C for clutter reconstruction can be seen in Embodiment 2, and will not be described in detail here. One possible way to reconstruct the clutter signals is to obtain reconstructed clutter signals based on the reconstructed matrix P1and the grouped channel estimation results G. Alternatively, one possible method of reconstructing the clutter signals is to obtain reconstructed clutter signals based on the reconstructed matrices P2and C, and the grouped channel estimation results G.

[0230] S705: The sensing node removes the reconstructed clutter signals (first clutter removal) from the grouped channel estimation results G to acquire channel estimation results Grafter clutter removal. Specifically, the method of removal may be .

[0231] S706: The sensing node rearranges elements in the channel results Grafter clutter removal to obtain . One possible arrangement is shown in Fig. 9; each group of elements in the first column in Gr(each group of elements contains Ns sample points) is arranged in a column of Hr1by indexes {1,Ng+1,2Ng+1,…Np-Ng+1}, each group of elements in the second column in Gr(each group of elements contains Ns sample points) is arranged in a column of Hr1by indexes {2,Ng+2,2Ng+2,…Np-Ng+2}, and so on, each group of elements in the Ng-th column in Gr(each group of elements contains Ns sample points) is arranged in a column of Hr1by indexes {Ng,2Ng,3Ng,…Np}, and finally constituting the channel estimation results Hr1after clutter removal.

[0232] S707: The sensing node may apply a target detection algorithm to the channel estimation results Hr1to detect and estimate parameters of the desired target object. Specifically, the sensing node may obtain a signal in the delay domain by performing an IDFT on Hr1column by column, obtain a signal in the Doppler domain by performing a DFT row by row, and detect a distance or velocity (Doppler frequency) of a single or a plurality of target objects by fixed threshold detection; the distance may be obtained by multiplying the delay by the speed of light and then being divided by two, and the velocity may be obtained by multiplying the Doppler frequency by the wavelength of the sensing signal and then being divided by two.

[0233] Embodiment 4

[0234] According to Embodiment 1, a method for a communication and sensing node to perform second clutter estimation and second clutter removal is shown in Fig. 10:

[0235] S901: The sensing node obtains a 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, the sensing signal may be a symbol based on OFDM modulation. Specifically, the constructed clutter subspace can be expressed as , where is the reference signal corresponding to the k -th sub-carrier in the frequency domain signal of the i -th sensing signal, Npis the number of sensing signals, and Nsis the number of sub-carriers of the frequency domain signal of the sensing signals. Based on the clutter subspace, the communication and sensing node can obtain the projection matrix of the clutter subspace, and when the number of sub-carriers is Ns, the communication and sensing node can obtain the projection matrix clutter subspaces.

[0236] S902: The sensing node reconstructs the clutter signal based on the projection matrix of the clutter subspace. The reconstruction method may be that the sensing node multiplies the channel estimation results with a projection matrix of a clutter subspace to obtain clutter signals. The channel estimation results are , where is a channel estimation result corresponding to a single sensing signal, the sensing signal can be a symbol modulated based on an OFDM symbol, and zi,i=1,...,Nsis a frequency domain estimation result corresponding to a single sub-carrier of a frequency domain sensing signal. H can be obtained in the manner of S701 and S702 in Embodiment 3, and will not be described in detail here. The sensing node obtains clutter signals

[0237] based on Nsprojection matrices of a clutter subspace, where , where is a frequency domain estimation result corresponding to a single sub-carrier of the frequency domain sensing signal.

[0238] S903: The sensing node removes the reconstructed clutter signals Hc2from the channel estimation results H (second clutter removal) to obtain channel estimation results Hr2after the clutter removal. Specifically, the method of removal may be .

[0239] S904: The sensing node may apply a target detection algorithm to the channel estimation results Hr2to detect and estimate parameters of the desired target object. Specifically, the sensing node may obtain a signal in the delay domain by performing an IDFT on Hrcolumn by column, obtain a signal in the Doppler domain by performing a DFT row by row, and detect a distance or velocity (Doppler frequency) of a single or a plurality of target objects by fixed threshold detection; the distance may be obtained by multiplying the delay by the speed of light and then being divided by two, and the velocity may be obtained by multiplying the Doppler frequency by the wavelength of the sensing signal and then being divided by two.

[0240] S905: Based on the target detection result of S904, the sensing node determines whether the target object satisfies the first condition, and if yes, proceeds to S906, and if not, the process is ended.

[0241] Specifically, the first condition may be at least one of the following:

[0242] (1) Determination is made as to whether the power of channel estimation results after the second clutter removal of a target object satisfies 0<p1<pi, and Doppler fi>0, where Ntis the number of sensing targets detected by a communication and sensing node, p1(unit: watt) is a fixed threshold, and Specifically, one possible value of p1is the power of noise floor, and the value of the power of noise floor can be a theoretical value or an actual measurement. The advantage of setting the condition in this way is that when the power of the channel estimation results after the second clutter removal of a real target object with a Doppler different from zero is greater than p1, a false target may be generated in the same distance corresponding thereto, and the condition can quickly screen out the real target object for which the false target may occur, and reduce the influence on target detection due to the clutter removal.

[0243] (2) Determination is made as to whether the power of channel estimation results after the second clutter removal of a target object satisfies 0<p1<pi, and Doppler , where Ntis the number of sensing targets detected by a communication and sensing node, pi(unit: watt) is a fixed threshold, fΔ(unit: hertz) is the Doppler resolution. Specifically, one possible value of piis the power of noise floor, and the value of the power of noise floor can be a theoretical value or an actual measurement. The advantage of setting the condition in this way is that when the Doppler of the real target object with the Doppler being different from zero is an integer multiple of the Doppler resolution, the power of the channel estimation results after the second clutter removal of the false target in the same distance corresponding thereto will be higher, and the condition can effectively screen out the real target object with the higher power of the channel estimation result after the second clutter removal of the false target, reduce the computational complexity of the clutter subspace projection matrix, and reduce the influence on the target detection due to the clutter removal.

[0244] (3) It is detected that the power of the channel estimation results after the second clutter removal of the target object corresponding to at least one of the preset distance and the preset angle is greater than the power of noise floor, and the detected Doppler frequency of the target object is not equal to 0.

[0245] (4) It is detected that the power of the channel estimation results after the second clutter removal of the target object corresponding to at least one of the preset distance and the preset angle is greater than the power of noise floor, and the detected Doppler frequency of the target object is an integer multiple of non-zero Doppler resolution.

[0246] It is to be noted that when the power of the channel estimation results after the second clutter removal of the target object with the Doppler frequency being different from zero is higher, the clutter removal of S903 will lead to the occurrence of a false target, resulting in a high false alarm probability. Specifically, the Doppler frequency of the false target is zero, which is the same distance as that of the sensed target object with a detected non-zero Doppler frequency. The benefit of using the first condition to select a detection target that satisfies the condition is that the sensed target object that caused the false target can be simply screened out to suppress the effect caused by the false target (step 906).

[0247] S906: The sensing node obtains a new clutter subspace projection matrix based on the target detection results, and then performs S902. Specifically, the sensing node can construct a new clutter subspace based on the clutter subspace ; is the reference signal corresponding to the k -th sub-carrier in the frequency domain signal of the i -th sensing signal, Npis the number of sensing signals, and Nsis the number of sub-carriers of the frequency domain signals of the sensing signals, where , are the Doppler frequencies corresponding to the Nvdetected target objects with non-zero Doppler in S905, Tsis the signal duration of a sensing signal, and Npis the number of sensing signals. Based on the new clutter subspace, the communication and sensing node can obtain a projection matrix of the new clutter subspace, and when the number of sub-carriers is Ns, the communication and sensing node can obtain Nsprojection matrices of the new clutter subspace. It should be noted that the advantage of using the new clutter subspace projection to construct the clutter signals is that the false target generated by the target object with high Doppler frequency on the equidistant zero Doppler frequency can be effectively suppressed and the false alarm probability can be reduced.

[0248] Embodiment 5

[0249] According to Embodiment 1, a method for a communication and sensing node to determine whether to perform second clutter estimation and second clutter removal based on echo signals after first clutter removal is shown in Fig. 11:

[0250] S1001: The sensing node performs channel estimation on the echo signals to obtain channel estimation results . Specifically, one implementation method for obtaining channel estimation results is to perform a DFT on echo signals to obtain a time domain expression Yfof the echo signal, then performing channel estimation using an LS method to obtain , where a positive integer Npis the number of echoes received by a sensing node, and the positive integer Nsis the number of sampling points of a single echo, is a reference signal.

[0251] S1002: The sensing node performs the first clutter removal on the channel estimation results to acquire channel estimation results Hr1after the first clutter removal. It should be noted that the reconstruction matrix used for reconstructing the first clutter in the first clutter removal may be obtained based on the grouping described in Embodiment 2 (specifically described in S504, which will not be described in detail here); it is also possible to perform clutter feature extraction on the echo signals based on the received echoes of a plurality of groups of Npsensing signals in a conventional manner without grouping to obtain a clutter reconstruction matrix.

[0252] S1003: The sensing node determines whether the second condition is satisfied based on the channel estimation results Hr1after the first clutter removal, performs S1004 when the second condition is satisfied, and performs S1005 when the second condition is not satisfied.

[0253] Specifically, the second condition may be at least one of the following:

[0254] (1) The power (unit: watt) of noise floor of the channel estimation results Hr1after the first clutter removal is greater than p2+Δ; the value of p2(units: watt) may be the power of noise floor of the channel estimation results after performing the first clutter estimation and removal based on the channel estimation results, Δ (unit: watt) is a positive number greater than zero, the value of which depends on the target object perceived in the environment. Specifically, Δ can take a larger value when the target object is close and / or its RCS is higher; and Δ may take a value of 0 or less when the target object is far away and / or its RCS is small. When the power of noise floor of Hr1is greater than p2+Δ, it can reflect that the first clutter estimation results reconstructed based on the first clutter reconstruction matrix cannot reflect the clutter in the current environment any more, resulting in that the residual clutter component after the first clutter removal of the sensing node will affect the detection of the actual target object.

[0255] (2) The average power (unit: watt) of channel estimation results hr1corresponding to zero Doppler component after first clutter removal is greater than p3+Δ, where the value of p3(units: watt) may be the average power of the zero-Doppler component estimation results after clutter estimation and removal based on the channel estimation results, Δ (unit: watt) is a positive number greater than zero, the value of which depends on the target object perceived in the environment. Specifically, Δ may take a larger value when the target object is close and / or its RCS is higher; and Δ may take a value of 0 or less when the target object is far away and / or its RCS is small. When the average power of hr1is greater than p3+Δ, it can reflect that the first clutter estimation results reconstructed based on the first clutter reconstruction matrix cannot reflect the zero-Doppler clutter component (static state) in the current environment, resulting in that the residual zero-Doppler clutter component after the first clutter removal of the sensing node will affect the detection of the static actual target object.

[0256] (3) The highest power of the channel estimation results hr1corresponding to the zero Doppler component after the first clutter removal is greater than p4+Δ, where p4(unit: watt) may be the highest power of the zero-Doppler component estimation results after the first clutter estimation and removal based on the channel estimation results, Δ (unit: watt) is a positive number greater than zero, the value of which depends on the target object perceived in the environment. Specifically, Δ may take a larger value when the target object is close and / or its RCS is higher; and Δ may take a value of 0 or less when the target object is far away and / or its RCS is small. By determining whether the highest power of hr1is greater than p4+Δ, it can be determined simply and quickly whether the first clutter estimation results reconstructed based on the first clutter reconstruction matrix can also reflect the zero-Doppler clutter component (static state) in the current environment, resulting in that the residual zero-Doppler clutter component after the first clutter removal of the sensing node will affect the detection of the static actual target object.

[0257] (4) The power of noise floor corresponding to at least one of a preset distance and a preset angle in the channel estimation results after the first clutter removal is greater than or equal to a preset threshold value.

[0258] (5) The power of channel estimation results corresponding to a zero Doppler frequency corresponding to at least one of a preset distance and a preset angle in the channel estimation results after the first clutter removal is greater than or equal to a preset threshold value.

[0259] S1004: The sensing node performs second clutter estimation and second clutter removal on the channel estimation results to obtain channel estimation results Hr2after the second clutter removal. Specifically, the specific method of the second clutter estimation and the second clutter removal may be the method described in Embodiment 4; it may also be a conventional way of clutter estimation and removal that does not include S905 and S906.

[0260] S1005: The sensing node may apply a target detection algorithm to the channel estimation results Hr2to detect and estimate parameters of the desired target object. Specifically, the sensing node may obtain a signal in the delay domain by performing an IDFT on Hr2column by column, obtain a signal in the Doppler domain by performing a DFT row by row, and detect a distance or velocity (Doppler frequency) of a single or a plurality of target objects by fixed threshold detection; the distance may be obtained by multiplying the delay by the speed of light and then being divided by two, and the velocity may be obtained by multiplying the Doppler frequency by the wavelength of the sensing signal and then being divided by two.

[0261] It should be noted that the optional solutions provided in the various embodiments of the present disclosure described above may be implemented separately, or the steps of each embodiment or each embodiment may be implemented in combination, without conflicting the implementation steps of the different embodiments.

[0262] Embodiments of the present disclosure also provide a node that may include a transceiver and at least one processor coupled to the transceiver that may perform the solutions provided by any of the alternative embodiments of the present disclosure, based on the same principles as methods provided by embodiments of the present disclosure. The node may be any electronic device, such as UE or a network node.

[0263] Optionally, the node may be a first node and at least one processor may be configured to perform any of the methods performed by the first node provided by embodiments of the present disclosure.

[0264] The embodiments of the present disclosure further provide an electronic device, the electronic device including at least one transceiver and at least one processor coupled to at least one transceiver, at least one processor is configured to perform the methods provided in any of the optional embodiments of the present disclosure.

[0265] FIG. 12 shows a schematic structure diagram of an electronic device to which the solution of the embodiment of the present disclosure is applied. As shown in FIG. 12, the electronic device 4000 shown in FIG. 12 may include a processor 4001 and a memory 4003. The processor 4001 is connected to the memory 4003, for example, through 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 other electronic devices, for example, data transmission and / or data reception. It should be noted that, in practical applications, the number of the transceivers 4004 is not limited to one, and the structure of the electronic device 4000 does not constitute any limitations to the embodiments of the present disclosure. Optionally, the electronic device may be a node in the wireless communication system, e.g., a first node. The node in the network may be user equipment and may also be a base station or other network node.

[0266] 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), or a field programmable gate array (FPGA), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It may implement or execute various exemplary logical blocks, modules and circuits described in connection with the present disclosure. The processor 4001 may also be a combination for realizing computing functions, for example, a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0267] The bus 4002 may include a path to transfer information between the components described above. The bus 4002 may be a peripheral component interconnect (PCI) bus, or an extended industry standard architecture (EISA) bus, etc. The bus 4002 may be an address bus, a data bus, a control bus, etc. For ease of presentation, the bus is represented by only one thick line in FIG. 12. However, it does not mean that there is only one bus or one type of buses.

[0268] The memory 4003 may be, but is not limited to, read only memories (ROMs) or other types of static storage devices that can store static information and instructions, random access memories (RAMs) or other types of dynamic storage devices that can store information and instructions, may be electrically erasable programmable read only memories (EEPROMs), compact disc read only memories (CD-ROMs) or other optical disk storages, optical disc storages (including compact discs, laser discs, discs, digital versatile discs, blu-ray discs, etc.), magnetic storage media or other magnetic storage devices, or any other media that can carry or store desired programs and that can be accessed by computers.

[0269] The memory 4003 is used to store application programs for executing the embodiments of the present disclosure, and is controlled by the processor 4001. The processor 4001 is used to execute the application programs stored in the memory 4003 to implement the steps of the foregoing method embodiments.

[0270] Fig. 13 is a block diagram of an internal configuration of a UE, according to an embodiment. Furthermore, the UE of Fig. 13 corresponds to the UE of Fig. 3.

[0271] As shown in Fig. 13, the UE according to an embodiment may include a transceiver 1310, a memory 1320, and a processor 1330. The transceiver 1310, the memory 1320, and the processor 1330 of the UE may operate according to a 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 those described above. In addition, the processor 1330, the transceiver 1310, and the memory 1320 may be implemented as a single chip. Also, the processor 1330 may include at least one processor.

[0272] The transceiver 1310 collectively refers to a UE receiver and a UE transmitter, and may transmit / receive a signal to / from a base station or a network entity. The signal transmitted or received to or from the base station or a network entity may include control information and data. The transceiver 1310 may include a RF transmitter for up-converting and amplifying a frequency of a transmitted signal, and a RF receiver for amplifying low-noise and down-converting a frequency of a received signal. However, this is only an example of the transceiver 1310 and components of the transceiver 1310 are not limited to the RF transmitter and the RF receiver.

[0273] Also, the transceiver 1310 may receive and output, to the processor 1330, a signal through a wireless channel, and transmit a signal output from the processor 1330 through the wireless channel.

[0274] The memory 1320 may store a program and data required for operations of the UE. Also, the memory 1320 may store control information or data included in a signal obtained 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 storage media.

[0275] The processor 1330 may control a series of processes such that the UE operates as described above. For example, the transceiver 1310 may receive a data signal including a control signal transmitted by the base station or the network entity, and the processor 1330 may determine a result of receiving the control signal and the data signal transmitted by the base station or the network entity.

[0276] Fig. 14 is a block diagram of an internal configuration of a base station or a network entity, according to an embodiment. Furthermore, the base station or the network entity of the Fig. 14 corresponds to the BS of the Fig. 2.

[0277] As shown in Fig. 14, the base station or the network entity according to an embodiment may include a transceiver 1410, a memory 1420, and a processor 1430. The transceiver 1410, the memory 1420, and the processor 1430 of the base station or the network entity may operate according to a communication method of the base station or the network entity described above. However, the components of the base station or the network entity are not limited thereto. For example, the base station or the network entity may include more or fewer components than those described above. In addition, the processor 1430, the transceiver 1410, and the memory 1420 may be implemented as a single chip. Also, the processor 1430 may include at least one processor.

[0278] The transceiver 1410 collectively refers to the base station(or the network entity receiver) and a base station(or the network entity) transmitter, and may transmit / receive a signal to / from a terminal or a network entity or a base station. The signal transmitted or received to or from the terminal or a network entity or the base station may include control information and data. The transceiver 1410 may include a RF transmitter for up-converting and amplifying a frequency of a transmitted signal, and a RF receiver for amplifying low-noise and down-converting a frequency of a received signal. However, this is only an example of the transceiver 1410 and components of the transceiver 1410 are not limited to the RF transmitter and the RF receiver.

[0279] Also, the transceiver 1410 may receive and output, to the processor 1430, a signal through a wireless channel, and transmit a signal output from the processor 1430 through the wireless channel.

[0280] The memory 1420 may store a program and data required for operations of the base station or the network entity. Also, the memory 1420 may store control information or data included in a signal obtained by the base station or the 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 storage media.

[0281] The processor 1430 may control a series of processes such that the base station or the network entity operates as described above. For example, the transceiver 1410 may receive a data signal including a control signal transmitted by the terminal or the network entity or the base station, and the processor 1430 may determine a result of receiving the control signal and the data signal transmitted by the terminal or the network entity or the base station.

[0282] Embodiments of the present disclosure provide a computer-readable storage medium having computer programs stored thereon that, when executed by a processor, implement steps and corresponding contents of the foregoing method embodiments.

[0283] Embodiments of the present disclosure further provide a computer program product including computer programs that, when executed by a processor, implement steps and corresponding contents of the foregoing method embodiments.

[0284] Terms such as "first", "second", "third", "fourth", "1" and "2" (if any) as used in the description, claims and drawings of the present disclosure are used to distinguish similar objects, and are not necessarily used to define a particular order or sequence. It should be understood that data, as used in such a way, may be used interchangeably if appropriate, so that the embodiments of the present disclosure described here may be implemented in an order other than those illustrated or described here.

[0285] It should be understood that although the steps in the flowchart of the embodiments of the present disclosure are sequentially indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. a In addition, based on actual implementation scenarios, some or all of the steps in the flowcharts may include multiple sub-steps or multiple stages. Some or all of the sub-steps or stages may be executed at the same moment of time, and each of the sub-steps or stages may be executed at different moments of time. In scenarios with different execution times, the execution order of these sub-steps or stages may be flexibly configured according to requirements, which is not limited in the embodiments of the present disclosure.

[0286] The above text and drawings are provided as examples only to help readers understand the present disclosure. They are not intended and should not be interpreted as limiting the scope of the present disclosure in any way. Although certain embodiments and examples have been provided, based on what is disclosed herein, it will be apparent to those skilled in the art that the embodiments and examples shown may be altered without departing from the scope of the present disclosure. Employing other similar means of implementation based on the technical ideas of the present disclosure also fall within the scope of protection of embodiments of the present disclosure.

Claims

1.A method performed by an apparatus in a wireless communication system, the method comprising:transmitting a first signal;receiving echo signals of the first signal;acquiring first clutter estimation results based on at least two groups of first channel estimation results, wherein the at least two groups of first channel estimation is acquired by performing channel estimation based on the echo signals; andperforming clutter removal on the at least two groups of first channel estimation results based on the first clutter estimation results to obtain second channel estimation results,wherein the at least two groups of first channel estimation results are obtained by at least one of the following operations:performing channel estimation on the echo signals to acquire third channel estimation results, and dividing at least one third channel estimation result obtained at each interval of a preset interval value from among the third channel estimation results into a same group, to acquire the at least two groups of first channel estimation results obtained by dividing the channel estimation results; anddividing at least one echo signal obtained at each interval of the preset interval value from among the echo signals into a same group to acquire at least two groups of echo signals, and performing channel estimation on the at least two groups of echo signals, to acquire the at least two groups of first channel estimation results obtained by dividing the echo signals.2.The method of claim 1, wherein the interval value is determined based on a Doppler frequency distribution of non-target objects.3.The method of claim 1, further comprising based on determination to perform clutter estimation based on the second channel estimation results, performing at least one of the following:performing clutter estimation based on at least one of the first signal and the third channel estimation results to obtain second clutter estimation results, and performing clutter removal on the third channel estimation results based on the second clutter estimation results to obtain fourth channel estimation results, to perform target detection based on at least one of the second channel estimation results and the fourth channel estimation results; andperforming clutter estimation based on at least one of the first signal and the at least two groups of first channel estimation results obtained by dividing the echo signals to obtain third clutter estimation results, and performing clutter removal on the at least two groups of first channel estimation results obtained by dividing the echo signals based on the third clutter estimation results to obtain fifth channel estimation results, to perform target detection based on at least one of the second channel estimation results and the fifth channel estimation results.4.The method of claim 3,wherein the performing clutter estimation based on at least one of the first signal and the third channel estimation results to obtain second clutter estimation results, and the performing clutter removal on the third channel estimation results based on the second clutter estimation results to obtain fourth channel estimation results includes:constructing a first matrix of a clutter subspace based on at least one of a frequency domain signal of the first signal and the third channel estimation results;performing signal reconstruction based on the first matrix and the third channel estimation results to acquire reconstructed second clutter estimation results; andperforming clutter removal on the third channel estimation results based on the second clutter estimation results to obtain the fourth channel estimation results; andwherein the performing clutter estimation based on at least one of the first signal and the at least two groups of first channel estimation results obtained by dividing the echo signals to obtain third clutter estimation results, and the performing clutter removal on the at least two groups of first channel estimation results obtained by dividing the echo signals based on the third clutter estimation results to obtain fifth channel estimation results includes:constructing a second matrix of the clutter subspace based on at least one of the frequency domain signal of the first signal and the at least two groups of first channel estimation results obtained by dividing the echo signals;performing signal reconstruction based on the second matrix and the at least two groups of first channel estimation results obtained by dividing the echo signals to acquire reconstructed third clutter estimation results; andperforming, based on the third clutter estimation results, clutter removal on the at least two groups of first channel estimation results obtained by dividing the echo signals, to obtain the fifth channel estimation results.5.The method of claim 4, further comprising:determining whether the target detection based on the fourth channel estimation results or the fifth channel estimation results satisfies a first condition;in case that the first condition is satisfied, constructing a third matrix of the clutter subspace based on results of the target detection;performing signal reconstruction based on the third matrix and the third channel estimation results to acquire reconstructed fourth clutter estimation results; or performing signal reconstruction based on the third matrix and the at least two groups of first channel estimation results obtained by dividing the echo signals, to obtain fifth clutter estimation results; andperforming clutter removal on the third channel estimation results based on the fourth clutter estimation results to obtain sixth channel estimation results; or performing clutter removal on the at least two groups of first channel estimation results obtained by dividing the echo signals based on the fifth clutter estimation results, to obtain a seventh channel estimation results, andwherein the first condition includes at least one of the following:it is detected that the power of the fourth channel estimation results or the fifth channel estimation results of a target object is greater than the power of noise floor, and a detected Doppler frequency of the target object is not equal to 0,it is detected that the power of the fourth channel estimation results or the fifth channel estimation results of the target object is greater than the power of noise floor, and the detected Doppler frequency of the target object is an integer multiple of non-zero Doppler resolution,it is detected that the power of the fourth channel estimation results or the fifth channel estimation results of the target object corresponding to at least one of a preset distance and a preset angle is greater than the power of noise floor, and the detected Doppler frequency of the target object is not equal to 0, andit is detected that the power of the fourth channel estimation results or the fifth channel estimation results of the target object corresponding to at least one of the preset distance and the preset angle is greater than the power of noise floor, and the detected Doppler frequency of the target object is an integer multiple of non-zero Doppler resolution.6.The method of claim 3,wherein the determination to perform clutter estimation based on the second channel estimation results includes:determining whether the second channel estimation results satisfy a preset second condition;determining to perform clutter estimation if the second channel estimation results satisfy the second condition; andperforming target detection based on the second channel estimation results if the second channel estimation results do not satisfy the second condition, andwherein the second condition includes at least one of the following:the power of noise floor of the second channel estimation results is greater than or equal to a preset threshold value;the power of channel estimation results corresponding to a zero Doppler frequency in the second channel estimation results is greater than or equal to the preset threshold value;the power of noise floor corresponding to at least one of a preset distance and a preset angle in the second channel estimation results is greater than or equal to the preset threshold value; andthe power of channel estimation results corresponding to a zero Doppler frequency corresponding to at least one of a preset distance and a preset angle in the second channel estimation results is greater than or equal to the preset threshold value.7.The method of claim 6, wherein the preset threshold value is related to at least one of a detected distance of a target object or radar cross-section (RCS) of the target object.8.An apparatus in a wireless communication system, the apparatus comprising:a transceiver; anda controller coupled to the transceiver, wherein the controller is configured to cause the apparatus to:transmit a first signal,receive echo signals of the first signal,acquire first clutter estimation results based on at least two groups of first channel estimation results, wherein the at least two groups of first channel estimation is acquired by performing channel estimation based on the echo signals, andperforming clutter removal on the at least two groups of first channel estimation results based on the first clutter estimation results to obtain second channel estimation results,wherein the at least two groups of first channel estimation results are obtained by at least one of the following operations:performing channel estimation on the echo signals to acquire third channel estimation results, and dividing at least one third channel estimation result obtained at each interval of a preset interval value from among the third channel estimation results into a same group, to acquire the at least two groups of first channel estimation results obtained by dividing the channel estimation results; anddividing at least one echo signal obtained at each interval of the preset interval value from among the echo signals into a same group to acquire at least two groups of echo signals, and performing channel estimation on the at least two groups of echo signals, to acquire the at least two groups of first channel estimation results obtained by dividing the echo signals.9.The apparatus of claim 8, wherein the interval value is determined based on a Doppler frequency distribution of non-target objects.10.The apparatus of claim 8, wherein the controller is further configured to cause the apparatus to, based on determination to perform clutter estimation based on the second channel estimation results:perform clutter estimation based on at least one of the first signal and the third channel estimation results to obtain second clutter estimation results, and performing clutter removal on the third channel estimation results based on the second clutter estimation results to obtain fourth channel estimation results, to perform target detection based on at least one of the second channel estimation results and the fourth channel estimation results, andperform clutter estimation based on at least one of the first signal and the at least two groups of first channel estimation results obtained by dividing the echo signals to obtain third clutter estimation results, and performing clutter removal on the at least two groups of first channel estimation results obtained by dividing the echo signals based on the third clutter estimation results to obtain fifth channel estimation results, to perform target detection based on at least one of the second channel estimation results and the fifth channel estimation results.11.The apparatus of claim 10,wherein the performing clutter estimation based on at least one of the first signal and the third channel estimation results to obtain second clutter estimation results, and the performing clutter removal on the third channel estimation results based on the second clutter estimation results to obtain fourth channel estimation results includes:constructing a first matrix of a clutter subspace based on at least one of a frequency domain signal of the first signal and the third channel estimation results,performing signal reconstruction based on the first matrix and the third channel estimation results to acquire reconstructed second clutter estimation results, andperforming clutter removal on the third channel estimation results based on the second clutter estimation results to obtain the fourth channel estimation results, andwherein the performing clutter estimation based on at least one of the first signal and the at least two groups of first channel estimation results obtained by dividing the echo signals to obtain third clutter estimation results, and the performing clutter removal on the at least two groups of first channel estimation results obtained by dividing the echo signals based on the third clutter estimation results to obtain fifth channel estimation results includes:constructing a second matrix of the clutter subspace based on at least one of the frequency domain signal of the first signal and the at least two groups of first channel estimation results obtained by dividing the echo signals,performing signal reconstruction based on the second matrix and the at least two groups of first channel estimation results obtained by dividing the echo signals to acquire reconstructed third clutter estimation results, andperforming, based on the third clutter estimation results, clutter removal on the at least two groups of first channel estimation results obtained by dividing the echo signals, to obtain the fifth channel estimation results.12.The apparatus of claim 11, wherein the controller is further configured to cause the apparatus to:determine whether the target detection based on the fourth channel estimation results or the fifth channel estimation results satisfies a first condition,in case that the first condition is satisfied, constructing a third matrix of the clutter subspace based on results of the target detection,perform signal reconstruction based on the third matrix and the third channel estimation results to acquire reconstructed fourth clutter estimation results; or performing signal reconstruction based on the third matrix and the at least two groups of first channel estimation results obtained by dividing the echo signals, to obtain fifth clutter estimation results, andperform clutter removal on the third channel estimation results based on the fourth clutter estimation results to obtain sixth channel estimation results; or performing clutter removal on the at least two groups of first channel estimation results obtained by dividing the echo signals based on the fifth clutter estimation results, to obtain a seventh channel estimation results, andwherein the first condition includes at least one of the following:it is detected that the power of the fourth channel estimation results or the fifth channel estimation results of a target object is greater than the power of noise floor, and a detected Doppler frequency of the target object is not equal to 0,it is detected that the power of the fourth channel estimation results or the fifth channel estimation results of the target object is greater than the power of noise floor, and the detected Doppler frequency of the target object is an integer multiple of non-zero Doppler resolution,it is detected that the power of the fourth channel estimation results or the fifth channel estimation results of the target object corresponding to at least one of a preset distance and a preset angle is greater than the power of noise floor, and the detected Doppler frequency of the target object is not equal to 0, andit is detected that the power of the fourth channel estimation results or the fifth channel estimation results of the target object corresponding to at least one of the preset distance and the preset angle is greater than the power of noise floor, and the detected Doppler frequency of the target object is an integer multiple of non-zero Doppler resolution.13.The apparatus of claim 10,wherein the determination to perform clutter estimation based on the second channel estimation results includes:determining whether the second channel estimation results satisfy a preset second condition;determining to perform clutter estimation if the second channel estimation results satisfy the second condition; andperforming target detection based on the second channel estimation results if the second channel estimation results do not satisfy the second condition, andwherein the second condition includes at least one of the following:the power of noise floor of the second channel estimation results is greater than or equal to a preset threshold value;the power of channel estimation results corresponding to a zero Doppler frequency in the second channel estimation results is greater than or equal to the preset threshold value;the power of noise floor corresponding to at least one of a preset distance and a preset angle in the second channel estimation results is greater than or equal to the preset threshold value; andthe power of channel estimation results corresponding to a zero Doppler frequency corresponding to at least one of a preset distance and a preset angle in the second channel estimation results is greater than or equal to the preset threshold value.14.The apparatus of claim 13, wherein the preset threshold value is related to at least one of a detected distance of a target object or radar cross-section (RCS) of the target object.

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