Target sensing method based on section trajectory, communication device, and storage medium

Abstract

The present application provides a target sensing method, a communication device, and a storage medium based on a partition trajectory, which includes the steps of: calculating a delay Doppler spectrum of a received signal received for each sensing signal period, and obtaining a comprehensive delay Doppler spectrum of each received signal containing all target information; partitioning the comprehensive delay Doppler spectrum, and preferentially selecting and extracting angle information to obtain a delay arrival angle spectrum of a prioritized multi-target of the partition; determining a movement trajectory according to a timing sequence of the delay arrival angle spectrum of a prioritized multi-target of the partition; and determining a moving target according to the movement trajectory.

Description

[Technical field]

[0001] This application is filed based on a Chinese patent application bearing application number 202211182526.7 and filing date September 27, 2022, and claims priority to the Chinese patent application, the entire contents of which are incorporated herein by reference.

[0002] TECHNICAL FIELD The embodiments of the present application relate to the technical field of communications, and in particular to a target sensing method based on a segment trajectory, a communication device, and a storage medium. [Background technology]

[0003] In related art, it is very difficult to realize ubiquitous sensing in a complex environment. Specifically, since there are many reflectors in a complex environment, there are often multiple propagation paths, the energy of the reflected signal may be larger than the energy of the echo signal of the moving object, and the reflected signal and the echo signal are not very separated in terms of speed, angle, or distance, so that it is difficult to accurately realize wireless sensing of moving objects in a complex environment. Summary of the Invention [Problem to be solved by the invention]

[0004] SUMMARY OF THE DISCLOSURE The embodiments of the present application provide a target sensing method, a communication device, and a storage medium based on a segment trajectory, aimed at achieving accurate wireless sensing of moving targets in complex environments. [Means for solving the problem]

[0005] According to a first aspect, the present embodiment comprises: Calculating a delay Doppler spectrum of a received signal for each sensing signal period to obtain an overall delay Doppler spectrum of each received signal including all target information, the overall delay Doppler spectrum including angle information; partitioning the total delay Doppler spectrum and preferentially selecting and extracting the angle information to obtain a delay angle of arrival spectrum of the preferred multi-targets of the partition; determining a movement trajectory according to the timing sequence of the delay arrival angle spectrum of the priority multi-targets of the section; determining a moving target according to the movement trajectory.

[0006] According to a second aspect, the present embodiment comprises: At least one processor; at least one memory storing at least one program; The at least one program, when executed by the at least one processor, performs the target sensing method based on the section trajectory according to any one of the first aspects.

[0007] According to a third aspect, the present embodiment comprises: There is provided a computer-readable storage medium having stored thereon a processor-executable program which, when executed by a processor, performs the target sensing method based on the section trajectory according to any one of the first aspects.

[0008] According to a fourth aspect, the present embodiment comprises: A computer program or computer instructions stored on a computer readable storage medium, A computer program product is provided in which a processor of a computer device reads the computer program or the computer instructions from the computer-readable storage medium and executes the computer program or the computer instructions to cause the computer device to perform a target sensing method based on a partition trajectory described in any one of the first aspect. Effect of the Invention

[0009] According to the target sensing method, communication device, and storage medium based on the partition trajectory of the embodiment of the present application, first, the delay Doppler spectrum of the received signal received for each sensing signal period is calculated to obtain the overall delay Doppler spectrum of each received signal including all target information, and the overall delay Doppler spectrum includes angle information. Next, the overall delay Doppler spectrum is partitioned, and the angle information is preferentially selected and extracted to obtain the delay arrival angle spectrum of the priority multi-target of the partition. Then, the movement trajectory is determined according to the timing sequence of the delay arrival angle spectrum of the priority multi-target of the partition. Finally, the moving target is determined according to the movement trajectory. In the embodiment of the present application, the delay Doppler spectrum of the received signal is calculated for each sensing signal period, and the overall delay Doppler spectrum is partitioned, preferentially selected, and extracted, so that the delay arrival angle spectrum of the priority multi-target of the partition can be obtained. Since the angle information and timing sequence of the multi-target are recorded in the above delay arrival angle spectrum, the movement trajectory and the corresponding moving target can be determined according to the change trend of the angle information and timing sequence corresponding to the multi-target in the multiple delay arrival angle spectra, and the influence of the interfering target can be eliminated. This makes it possible to accurately realize wireless sensing of moving targets in complex environments. [Brief description of the drawings]

[0010] [Figure 1] FIG. 1 is a schematic diagram illustrating people sensing in a terrestrial scenario according to an embodiment of the present application. [Diagram 2] FIG. 2 is a schematic diagram illustrating vehicle sensing in a ground scenario according to one embodiment of the present application. [Diagram 3] 1 is a schematic diagram of a communication system for implementing a target sensing method based on a section trajectory according to an embodiment of the present application; [Figure 4] 2 is a flowchart of a target sensing method based on a segment trajectory according to an embodiment of the present application; [Diagram 5]4 is a flowchart of a target sensing method based on segment trajectory according to another embodiment of the present application. [Figure 6] 4 is a flowchart of a target sensing method based on segment trajectory according to another embodiment of the present application. [Figure 7] 4 is a flowchart of a target sensing method based on segment trajectory according to another embodiment of the present application. [Figure 8] 4 is a flowchart of a target sensing method based on segment trajectory according to another embodiment of the present application. [Figure 9] 4 is a flowchart of a target sensing method based on segment trajectory according to another embodiment of the present application. [Figure 10] 4 is a flowchart of a target sensing method based on segment trajectory according to another embodiment of the present application. [Figure 11] 4 is a flowchart of a target sensing method based on segment trajectory according to another embodiment of the present application. [Figure 12] 4 is a flowchart of a target sensing method based on segment trajectory according to another embodiment of the present application. [Figure 13] 4 is a flowchart of a target sensing method based on segment trajectory according to another embodiment of the present application. [Figure 14] 4 is a schematic diagram showing the relationship between a sensing period, a sensing signal period, and a sensing signal length according to an embodiment of the present application; [Figure 15] 4 is a schematic diagram of the relationship between the section width, the sensing signal length, and the sensing signal sampling period according to an embodiment of the present application. [Figure 16] FIG. 2 is a schematic diagram of a delayed arrival angle spectrum of a sensing target according to an embodiment of the present application. [Figure 17] 1 is a schematic diagram of a delayed arrival angle spectrum of a sensing target for multiple consecutive sensing periods according to an embodiment of the present application; FIG. [Figure 18] FIG. 2 is a schematic diagram illustrating sensing of a moving target based on curve fitting trajectory according to an embodiment of the present application; [Figure 19]FIG. 2 is a schematic diagram illustrating an implementation scenario of a person walking according to an embodiment of the present application; [Figure 20] FIG. 2 is a schematic diagram of Doppler domain data in a human walking implementation scenario according to one embodiment of the present application; [Figure 21] FIG. 2 is a schematic diagram of a trajectory drawn in an implementation scenario of a person walking according to an embodiment of the present application; [Figure 22] FIG. 1 is a schematic diagram of an implementation scenario in which a drone flies according to an embodiment of the present application. [Diagram 23] FIG. 1 is a schematic diagram of a trajectory drawn in an implementation scenario in which a drone flies according to an embodiment of the present application. [Figure 24] FIG. 1 is a schematic diagram illustrating a configuration of a communication device according to an embodiment of the present application. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be described in more detail below with reference to the drawings and examples. The specific examples described in this specification are only used to interpret the present application, and are not used to limit the present application.

[0012] Although the functional modules are divided in the schematic diagram of the device and a logical order is shown in the flowchart, in some cases the division of the modules in the device may be different, or the steps shown or described may be performed in a different order from that in the flowchart. The terms "first", "second", etc. in this specification and claims and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or priority.

[0013] In the embodiments of the present application, terms such as "further," "exemplary," or "optionally" are used as an example, illustration, or description and should not be construed as preferred or advantageous over other embodiments or designs. Use of terms such as "further," "exemplary," or "optionally" is intended to present the associated concept in a concrete manner.

[0014] In terms of related technologies, we are currently in the era of the Fourth Industrial Revolution, and an important feature of the Fourth Industrial Revolution is ubiquitous intelligence. On the one hand, intelligent technology penetrates deeply into people's lives, bringing great convenience and new experiences to people's lives; on the other hand, intelligent technology penetrates deeply into all industries, realizing industrial upgrading and improving industrial efficiency through intelligence. The development in both directions will greatly liberate mankind and remove the shackles of low-level production.

[0015] Ubiquitous intelligent technology mainly includes ubiquitous sensing technology, ubiquitous computing technology, product research and development, etc. Therefore, ubiquitous intelligence requires ubiquitous systems, and among the currently implemented systems, only wireless communication networks meet the ubiquitous criteria, so the main technical means is to realize ubiquitous sensing and ubiquitous computing through wireless communication networks.

[0016] At present, in the field of sensing, detailed research has been mainly conducted in the field of radar, and the current application scenarios of radar equipment mainly include aircraft sensing, such as airport radar, and short-range sensing, such as vehicle-mounted radar. Both scenarios are simple scenarios. Ubiquitous sensing needs to be able to realize sensing in various complex scenarios, such as indoor multipath environments, multiple buildings on the ground, multiple vehicle environments, and multi-person environments in shopping malls. As shown in Figures 1 and 2, Figure 1 is a schematic diagram showing human sensing in a ground scenario according to an embodiment of the present application. Figure 2 is a schematic diagram showing vehicle sensing in a ground scenario according to an embodiment of the present application. Here, the shaded area in the dotted area in Figure 2 is the area where interference sensing signals exist, and it is difficult to accurately distinguish moving targets and interference targets from this area. At present, there is little research on sensing of complex environments, and even fewer sensing technologies that can be commercialized. Sensing of complex environments is a research hotspot in both the standardization community and the academic community, and is in the early stages of technological breakthrough.

[0017] Wireless sensing technologies vary greatly depending on the scenario. For sensing in low-altitude environments, such as drone sensing, the background is simple, so generally there are only echo signals of the sensing target, and the signal separation is very good in terms of distance, angle, and speed, making it easy to separate and identify. On the other hand, for the ground, there are many different reflectors, and generally there is multipath, usually more than 10 propagation paths in most cases, and in many cases the energy of the reflected signal from the environment is greater than the echo signal of the moving object. On the ground, the signals of the sensing target and the signals reflected from the environment are not very separated in terms of speed, angle, and distance, and are often mixed, which makes traditional wireless sensing very difficult.

[0018] On this basis, the present application provides a target sensing method based on a partition trajectory, a communication device, a computer-readable storage medium, and a computer program product, which can determine a moving target among multiple targets in a complex scenario, can eliminate the influence of an interfering target among multiple targets, and can accurately realize wireless sensing of moving targets in a complex environment.

[0019] 3 is a schematic diagram of a communication system for implementing a target sensing method based on a block trajectory according to an embodiment of the present application. The communication system includes a transmitting node 110, a sensing target 120, and a receiving node 130, among which the sensing target 120 includes, but is not limited to, a moving sensing target 121 whose position moves over time and an interference sensing target 122 whose position is fixed.

[0020] In one embodiment, as shown in Fig. 3, the wireless signal of the transmitting node 110 is directly transmitted to the receiving node 130 via the mobile sensing target 121, and is indirectly transmitted to the receiving node 130 via the interference sensing target 122. Alternatively, in one embodiment, the wireless signal of the transmitting node 110 is directly transmitted to the receiving node 130 via the mobile sensing target 121, and may be indirectly transmitted to the receiving node 130 sequentially via the mobile sensing target 121 and the interference sensing target 122. In the embodiment of the present application, the path and method of the wireless signal between the transmitting node 110 and the receiving node 130 passing through the mobile sensing target 121 and the interference sensing target 122, respectively, are not particularly limited.

[0021] The number of moving sensing targets 121 in the technical solution of the embodiments of the present application may be one or more, and the number of interference sensing targets 122 may also be one or more, and the numbers of moving sensing targets 121 and interference sensing targets 122 in the embodiments of the present application are not particularly limited.

[0022] The technical solutions of the embodiments of the present application may be applied to various communication systems, such as wideband code division multiple access (WCDMA), evolved universal terrestrial radio access network (E-UTRAN) systems, next generation radio access network (NG-RAN) systems, long term evolution (LTE) systems, worldwide interoperability for microwave access (WiMAX) communication systems, 5th Generation (5G) systems, new radio access technology (NR), and future communication systems such as 6G systems.

[0023] The technical solutions of the embodiments of the present application can be applied to various communication technologies such as microwave communication, light wave communication, millimeter wave communication, etc. The embodiments of the present application are not limited to the specific technologies or the specific forms of the devices used.

[0024] The transmitting node 110 in the embodiment of the present application may be an evolved base station (eNB: evolved NodeB), a transmission reception point (TRP: Transmission Reception Point), a next generation base station (gNB: Next Generation NodeB) in an NR system, a base station in other future mobile communication systems, a transmitting node in a wireless fidelity (WiFi: Wireless Fidelity) system, etc. The embodiment of the present application is not limited to a specific technology adopted by the transmitting node or a specific form of equipment.

[0025] The mobile sensing target 121 in the embodiment of the present application is a user-side entity such as a mobile phone for transmitting and receiving signals. It may also be called a receiving node device (terminal), user equipment (UE), mobile station (MS), mobile receiving node device (MT), etc. The receiving node device may be an automobile with a communication function, a smart car, a mobile phone, a wearable device, a tablet computer (Pad), a computer with a wireless transmission and reception function, a virtual reality (VR) receiving node device, an augmented reality (AR) receiving node device, a wireless receiving node device in industrial control, a wireless receiving node device in self-driving, a wireless receiving node device in transportation safety, a wireless receiving node device in a smart city, etc. The embodiment of the present application does not limit the specific technology adopted in the mobile sensing target or the specific form of the device.

[0026] The receiving node 130 in the embodiment of the present application may be an evolved base station (eNB: evolved NodeB), a transmission reception point (TRP: Transmission Reception Point), a next generation base station (gNB: Next Generation NodeB) in an NR system, a base station in other future mobile communication systems, a receiving node in a wireless fidelity (WiFi: Wireless Fidelity) system, etc. The embodiment of the present application is not limited to a specific technology adopted by the receiving node or a specific form of equipment.

[0027] Hereinafter, based on the communication system of any of the above embodiments, various embodiments of a target sensing method based on a section trajectory according to the embodiments of the present application will be proposed.

[0028] As shown in FIG. 4, FIG. 4 is a flowchart of a target sensing method based on a partition trajectory according to one embodiment of the present application, which may include, but is not limited to, the following steps S100, S200, S300, and S400.

[0029] Step S100: Calculate a delay Doppler spectrum of a received signal for each sensing signal period, and obtain an overall delay Doppler spectrum of each received signal containing all target information, where the overall delay Doppler spectrum contains angle information.

[0030] Step S200: The comprehensive delay Doppler spectrum is partitioned, and angle information is preferentially selected and extracted to obtain the delay arrival angle spectrum of the preferred multi-targets of the partition.

[0031] Step S300: Determine a movement trajectory according to the timing sequence of the delay arrival angle spectrum of the priority multi-targets in the section.

[0032] Step S400: A moving target is determined according to the movement trajectory.

[0033] In one embodiment of the present application, the delayed Doppler spectrum of the received signal is calculated for each sensing signal period to obtain a comprehensive delayed Doppler spectrum including angle information, and the comprehensive delayed Doppler spectrum is partitioned, preferentially selected, and extracted to obtain the delayed arrival angle spectrum of the prioritized multi-targets of the partition. Since the angle information and timing sequence of the multi-targets are recorded in the delayed arrival angle spectrum, the moving trajectory and the corresponding moving targets can then be determined according to the changing trend of the angle information and timing sequence corresponding to the multi-targets in the multiple delayed arrival angle spectra, and the influence of the interfering targets can be eliminated. Thus, wireless sensing of moving targets in a complex environment can be accurately realized.

[0034] In one embodiment, the number of sensing signal periods is multiple and each sensing signal period includes at least one received signal, but the embodiment of the present application does not particularly limit the number of sensing signal periods and received signals.

[0035] In one embodiment, the above-mentioned total delay Doppler spectrum corresponds to all target information, and the delay angle of arrival spectrum of the priority multi-targets of the zone corresponds to a part of the target information because it has undergone zone processing and priority selection processing, the part of the target information is the target information after screening, including but not limited to the moving target information after screening and the interference target information after screening.

[0036] In an embodiment of the present application, one or more movement trajectories may be estimated according to the timing sequence of the multiple delayed arrival angle spectra. Specifically, since the position of a moving target changes with time, its timing sequence in the multiple delayed arrival angle spectra also changes accordingly, and therefore the embodiment of the present application can obtain the movement trajectory of the moving target according to the timing sequence of the multiple delayed arrival angle spectra, where each movement trajectory corresponds to one moving target, and the existence of multiple movement trajectories indicates the existence of multiple moving targets.

[0037] Also, as shown in Fig. 5, Fig. 5 is a flowchart of a target sensing method based on a partition trajectory according to another embodiment of the present application. The above step S100 of calculating the delay Doppler spectrum of the received signal received at each sensing signal period and obtaining the overall delay Doppler spectrum of each received signal including all target information includes, but is not limited to, step S510 and step S520.

[0038] Step S510: Calculate the channel impulse response of the received signal for each sensing signal period received by each antenna, and obtain a channel impulse response vector corresponding to each antenna.

[0039] Step S520: Calculate the delay-Doppler spectrum of all channel impulse response vectors corresponding to all antennas, and obtain the overall delay-Doppler spectrum of each received signal containing all target information.

[0040] In one embodiment of the present application, a channel impulse response vector corresponding to each antenna may be calculated first, and then a delay Doppler spectrum may be calculated based on all the channel impulse response vectors corresponding to all the antennas to obtain a comprehensive delay Doppler spectrum.

[0041] In one embodiment, the antenna of the embodiment of the present application may be one or more, and the number of antennas is not particularly limited in the embodiment of the present application.

[0042] Also, as shown in Fig. 6, Fig. 6 is a flowchart of a target sensing method based on a partition trajectory according to another embodiment of the present application. The above step S520 of calculating the delay Doppler spectrum of all channel impulse response vectors corresponding to all antennas to obtain a comprehensive delay Doppler spectrum of each received signal containing all target information includes, but is not limited to, step S610 and step S620.

[0043] Step S610: Calculate the delay Doppler spectrum of the channel impulse response vector corresponding to each antenna, and obtain an initial delay Doppler spectrum containing all target information corresponding to each antenna.

[0044] Step S620: Perform directional filtering on all initial delay Doppler spectra corresponding to all antennas to obtain a comprehensive delay Doppler spectrum of each received signal containing all target information.

[0045] In one embodiment of the present application, an initial delay Doppler spectrum containing all target information corresponding to each antenna may be first calculated, and then directional filtering may be performed on all the initial delay Doppler spectra corresponding to all antennas based on different azimuth directions to screen the overall delay Doppler spectrum of each received signal containing all target information.

[0046] Also, as shown in Fig. 7, Fig. 7 is a flowchart of a target sensing method based on a partition trajectory according to another embodiment of the present application. The above step S510 of calculating a channel impulse response of a received signal for each sensing signal period received by each antenna and obtaining a channel impulse response vector corresponding to each antenna includes, but is not limited to, step S710 and step S720.

[0047] Step S710: Based on a preset sampling period, samples are performed for each received signal received by each antenna to obtain a plurality of sampling data.

[0048] Step S720: For each sensing signal period, obtain a channel impulse response vector corresponding to each antenna based on a plurality of sampling data corresponding to each antenna and the sensing signal transmitted within the sensing signal period.

[0049] In one embodiment of the present application, the channel impulse response vector corresponding to each antenna may be calculated by sampling. Specifically, first, each received signal received by each antenna is sampled for a time length of a preset sampling period, and the channel impulse response vector corresponding to each antenna may be calculated based on a plurality of sampling data and the sensing signal transmitted within the sensing signal period.

[0050] In one embodiment, the preset sampling period in the embodiment of the present application may be preset, and the embodiment of the present application does not particularly limit the specific time length of the preset sampling period.

[0051] Also, as shown in FIG. 8, FIG. 8 is a flowchart of a target sensing method based on a partition trajectory according to another embodiment of the present application. The above step S620 of performing directional filtering on all initial delay Doppler spectra corresponding to all antennas to obtain a comprehensive delay Doppler spectrum of each received signal containing all target information includes, but is not limited to, step S810, step S820, and step S830.

[0052] Step S810: A plurality of pieces of angle information are obtained.

[0053] Step S820: For each sensing signal period, calculate a composite delay Doppler spectrum at an angle corresponding to the angle information for the initial delay Doppler spectra of all antennas.

[0054] Step S830: Perform screening based on all the composite delay Doppler spectra in the sensing signal period to obtain a comprehensive delay Doppler spectrum including all the target information in the sensing signal period.

[0055] In one embodiment, the above-mentioned directional filtering process is specifically carried out by calculating a composite delayed Doppler spectrum of the initial delayed Doppler spectra of all antennas for each angle corresponding to each angle information for each sensing signal period, and then screening all composite delayed Doppler spectra within the sensing signal period according to the magnitude of their amplitudes to obtain a comprehensive delayed Doppler spectrum including all target information within the sensing signal period.

[0056] In one embodiment, the above angle information may include horizontal angle information, may include vertical angle information, or may include both horizontal and vertical angle information, but the embodiment of the present application is not particularly limited in terms of the type of angle information.

[0057] In one embodiment, each delay Doppler spectrum binary data in the overall delay Doppler spectrum is the delay Doppler spectrum binary data with the largest corresponding amplitude in the composite delay Doppler spectrum corresponding to all angles.

[0058] In one embodiment, in addition to the delayed Doppler spectrum binary data with the largest amplitude, the delayed Doppler spectrum binary data with the next largest amplitude may be used, or delayed Doppler spectrum binary data with another amplitude may be used, and in the embodiment of the present application, there is no particular limitation on the magnitude of the amplitude of the delayed Doppler spectrum binary data.

[0059] Also, as shown in Fig. 9, Fig. 9 is a flowchart of a target sensing method based on a partition trajectory according to another embodiment of the present application. The above step S200 of partitioning the comprehensive delay Doppler spectrum, and preferentially selecting and extracting angle information to obtain the delay arrival angle spectrum of the preferential multi-targets in the partition includes, but is not limited to, step S910, step S920, and step S930.

[0060] Step S910: The total delay Doppler spectrum is partitioned to obtain a plurality of partitions each including a plurality of delay Doppler spectrum binary data.

[0061] Step S920: According to the number of targets, preferentially select the priority delay Doppler spectrum binary data corresponding to each section from among all the delay Doppler spectrum binary data corresponding to each section.

[0062] Step S930: Extract angle information for all the priority delay Doppler spectrum binary data in each section, and obtain the delay arrival angle spectrum of the priority multi-targets in each section, where each priority delay Doppler spectrum binary data corresponds to one priority target.

[0063] In one embodiment of the present application, the total delay Doppler spectrum is divided into sections, delay Doppler spectrum binary data of a number of targets is selected from each section, and then angle information of the priority delay Doppler spectrum binary data is extracted to generate a delay arrival angle spectrum of the priority multi-targets in each section.

[0064] In one embodiment, the number of targets may be one or more, and the embodiment of the present application is not particularly limited to the number of targets.

[0065] Also, as shown in Fig. 10, Fig. 10 is a flowchart of a target sensing method based on a section trajectory according to another embodiment of the present application. The above step S920 of preferentially selecting the priority delayed Doppler spectrum binary data corresponding to each section among all the delayed Doppler spectrum binary data corresponding to each section according to the number of targets includes, but is not limited to, step S1010 and step S1020.

[0066] Step S1010: The amplitudes of all the delayed Doppler spectrum binary data corresponding to each section are sorted in ascending or descending order of values.

[0067] Step S1020: According to the number of targets, the sorted multiple delayed Doppler spectrum binary data corresponding to each section are preferentially selected in descending order to obtain prioritized delayed Doppler spectrum binary data corresponding to each section.

[0068] In one embodiment of the present application, the delayed Doppler spectrum binary data of the target number having the highest numerical value may be selected as the priority delayed Doppler spectrum binary data corresponding to each section.

[0069] Also, as shown in Fig. 11, Fig. 11 is a flowchart of a target sensing method based on a section trajectory according to another embodiment of the present application. The above step S300 of determining a movement trajectory according to the timing sequence of the delay arrival angle spectrum of the priority multi-targets of the section includes, but is not limited to, step S1110 and step S1120.

[0070] Step S1110: Determine the timing sequence of all delay arrival angle spectra based on multiple sensing signal periods.

[0071] Step S1120: According to the timing sequence, perform curve fitting for all delay arrival angle spectra to obtain at least one movement trajectory.

[0072] In one embodiment of the present application, curve fitting may be performed according to the timing sequence of the multiple delayed arrival angle spectra to obtain one or more moving trajectories. Specifically, since the position of the moving target changes with time, its timing sequence in the multiple delayed arrival angle spectra also changes accordingly, and thus the moving trajectory of the moving target can be obtained according to the timing sequence of the multiple delayed arrival angle spectra. Here, each moving trajectory corresponds to one moving target, and the existence of multiple moving trajectories indicates the existence of multiple moving targets.

[0073] Also, as shown in Fig. 12, Fig. 12 is a flowchart of a target sensing method based on a section trajectory according to another embodiment of the present application, which further includes, but is not limited to, step S1210 and step S1220 after the above step S400 of determining a moving target according to a moving trajectory.

[0074] Step S1210: Determine the inertial movement tendency of the moving target according to the movement trajectory.

[0075] Step S1220: Determine the position information of the moving target according to the inertial moving tendency and the delayed arrival angle spectrum of the prioritized multi-targets in the section corresponding to the next sensing signal period.

[0076] In one embodiment of the present application, by estimating the future inertial movement tendency of the moving target according to the movement trajectory, the position information of the moving target can be preferentially determined from the delayed arrival angle spectrum of the prioritized multi-target in the section corresponding to the next sensing signal period.

[0077] In one embodiment, the inertial movement tendency of a moving target in the embodiments of the present application may refer to the position that the moving target is about to arrive at or the trajectory that the moving target is about to move along.

[0078] Also, as shown in Fig. 13, Fig. 13 is a flowchart of a target sensing method based on a section trajectory according to another embodiment of the present application. This target sensing method based on a section trajectory further includes, but is not limited to, step S1300 after the above step S1120 of obtaining at least one movement trajectory.

[0079] Step S1300: If there is a target whose relative position change is smaller than a preset threshold among the priority multi-targets after partitioning in the multiple comprehensive delayed Doppler spectra, the target is determined to be an interfering target.

[0080] In one embodiment, if there is a target among the prioritized multi-targets after partitioning whose relative position change is less than a preset threshold, this indicates that the target's position has not changed over time, and in this case, in the embodiment of the present application, the target can be considered as an interfering target.

[0081] Hereinafter, based on the target sensing method based on the section trajectory according to any one of the above embodiments, specific embodiments of the target sensing method based on the section trajectory according to the embodiments of the present application will be proposed.

[0082] In a specific embodiment, the target sensing method based on the partition trajectory includes, but is not limited to, the following steps 1 to 8.

[0083] Step 1: A sensing signal transmitting base station transmits a sensing signal S on a configured radio resource according to a sensing signal period a2 within a3 according to a sensing period a3.

[0084] Step 2: Sensing signal reception The base station receives the current sensing signal y in the current sensing period z. Each receiving antenna signal R m.n For (t), sampling is performed according to a sampling period a4, and sampling is performed continuously within the symbol time length a1 to obtain one symbol of sampling data R m.n (i,y),i∈[0,a1 / a4), where m,n are the transducer numbers in the antenna array, m∈[0,M-1], n∈[0,N-1], and y is the currently received sensing signal period number, y∈[0,a3 / a2]. The relationship between the sensing period, the sensing signal period, and the sensing signal length is shown in Figure 14.

[0085] Receive signal sampling data for each antenna, and calculate the channel impulse response vector c for each antenna based on the transmitted signal s. m.n Get (i,y).

[0086] Step 3: In the current sensing period z, for all the received sensing signals (y is from 0 to a3 / a2-1), the delay-Doppler spectrum d m.n (i,x), where i denotes the sample number and x denotes the Doppler frequency, x∈[0,a3 / a2).

[0087] Step 4: All the d m.n Directional filtering is performed on (i,x) to obtain the maximum delay-Doppler spectrum M(i,x), and the angle corresponding to each (i,x) is recorded, where the value of M(i,x) is the value that makes M(i,x) the maximum amplitude value in all directional filtering, and the angle corresponding to the maximum amplitude value is the angle corresponding to M(i,x).

[0088] Step 5: M(i,x) is partitioned according to the delay partition width a5, and the number of detection targets per partition is K. Among all (i,x) within each partition of M(i,x) in the current sensing cycle z, the binaries of the top k largest peaks are taken as the k sensing targets within that partition, for example, from the k1th largest target to the k2nd largest target are selected, and K2-K1=K. The relationship between partition width, sensing signal length, and sensing signal sampling cycle is shown in Figure 15.

[0089] Every block has k*a1 / a5 targets. For every sensing target, the delay arrival angle spectrum P of the sensing target in that sensing period is calculated according to the corresponding angle and delay sample number. z (i,β) is formed, and k*a1 / a5 targets are found in the spectrum, and 0 is assigned where there are no targets. The delayed arrival angle spectrum of the sensing targets is shown in Figure 16.

[0090] The delayed arrival angle spectrum of the sensing target for this period may be selectively transmitted to the sensing server.

[0091] Step 6: Repeat steps 1 to 5 to obtain the delayed arrival angle spectrum P of the sensing target in the next sensing period. z+1 (i, β) is formed. By continuing to proceed, the delayed arrival angle spectrum of the sensing target in successive sensing cycles is obtained. The delayed arrival angle spectrum of the sensing target in multiple successive sensing cycles is shown in Figure 17.

[0092] Step 7: Perform curve fitting on the successive delayed arrival angle spectra, and determine the number of sensing targets according to the fitting curve, determine the movement trajectory of each sensing target, and determine the section of the interference region.

[0093] Here, a smooth and continuous curve may be formed to serve as one moving sensing target, or multiple smooth and continuous curves may be formed to serve as multiple moving sensing targets.

[0094] The sensing target area with relatively fixed angle and delay is taken as the interference area.

[0095] Curve fitting is optionally performed on the sensing server. A schematic diagram of curve fitting trajectory sensing moving target is shown in Figure 18.

[0096] Step 8: Based on the inertial tendency determined by the movement trajectory of the sensing target, preferentially determine the current position of the sensing target from the delay arrival angle spectrum of the sensing target in the subsequent sensing period.

[0097] Based on the above steps 1 to 8, some of steps 1 to 8 will be described in detail below.

[0098] For each antenna's received signal sampling data, the channel impulse response vector c for each antenna is calculated based on the transmitted signal s. m.n Step 2, "Get (i,y)" The method includes transforming the sampling data of each antenna into a frequency domain, then dividing each subcarrier received data by each transmitted subcarrier signal to obtain a frequency domain impulse response of each antenna, and then transforming it into a time domain to obtain a time domain impulse response.

[0099] Moreover, the step 3 of "calculating the delay-Doppler spectrum of the current sensing cycle" is specifically as follows. After obtaining the time-domain impulse responses of all sensing signals in one sensing period of each antenna, take the same delay sample number values ​​from the channel impulse responses of all sensing signals in the current sensing period, starting from delay sample number 0, respectively, and then perform Fourier transform to obtain the delay-Doppler spectrum of the current sensing period.

number

[0100] Also, "All d m.n Step 4 is to perform directional filtering for (i,x) to obtain the maximum delay-Doppler spectrum M(i,x) and record the angle corresponding to each (i,x). This involves performing directional filtering with a step size of Δθ in the azimuth angle interval [θ1, θ2] and with a step size of Δβ in the pitch angle interval [β1, β2].

number

[0101] In addition, the “top k largest peaks” in step 5 means that the amplitudes corresponding to all (i, x) binaries in the partition of M(i, x) are sorted in descending order, and the first K peaks are taken as the sensing targets.

[0102] According to the technical proposal of steps 1 to 8 above, compared with the conventional technology, it is possible to solve problems such as large sensing errors due to interference in a complex environment, mutual interference between the environment and the sensing target, mutual interference between multiple targets, etc. In the embodiment of the present application, it is possible to realize sensing of multiple targets and interference sections in a complex environment by trajectory sensing.

[0103] In another embodiment, in a scenario in which multi-target sensing is implemented, the sensing signal has a transmission period of 5 ms, a frequency of 4.9 GHz, and an area of ​​160 m in length and 90 m in width. There are two test paths 1 and 2 that are perpendicular to each other, and two test subjects (targets) walk along paths 1 and 2, respectively, as shown in FIG. 19 .

[0104] Thus, the process steps of the example are as follows:

[0105] The LFM sensing signal has a transmission period of 5 ms and a bandwidth of 100 M.

[0106]

number

[0107]

number

[0108] The angles are calculated, i.e., horizontally in the range of -90° to 90° and vertically in the range of -90° to 90°, and a steering vector is constructed for each angle, and the dot product and sum are calculated with the 32-element Doppler domain data. m.n Get (i,x). M m.n The maximum horizontal and vertical angles of (i,x) are the direction of arrival of the signal.

[0109] The distance is calculated, i.e., the Doppler domain data M m.n(i,x) has a distance range of 0 to 4096Ts and a frequency range of 0 to 200Hz. m=8 is the time section width, and k=4 is the number of detected targets. In the range of 0 to 4096Ts, one section is created every mTs, and the k largest Doppler amplitude data are searched within this section, and the distance T value is recorded. Then, the corresponding angle value is determined according to 4. The above is the sensing result of the distance and angle at the first second.

[0110] Drawing the trajectory: The above steps are repeated to obtain sensing results for one minute, and the trajectory is drawn as shown in Figure 21.

[0111] In another embodiment, the implementation scenario of interference area sensing is as follows: the transmission period of the sensing signal is 5 ms, the frequency is 4.9 GHz, and the drone must pass through two interference areas on the flight path, which have interference from the operation of a nearby fan fan and interference from the shaking of a few leaves in the distance. The flight path is shown in Figure 22.

[0112] Thus, the process steps of the example are as follows:

[0113] The LFM sensing signal has a transmission period of 5 ms and a bandwidth of 100 M.

[0114]

number

[0115]

number

[0116] The angles are calculated, i.e., horizontally in the range of 40° to 80° and vertically in the range of 0° to 20°, and a steering vector is constructed for each angle, and the dot product and sum are calculated with the 32 elements of Doppler domain data. m.n Get (i,x). M m.n The maximum horizontal and vertical angles of (i,x) are the direction of arrival of the signal.

[0117] The distance is calculated, i.e., the Doppler domain data M m.n (i,x) has a distance range of 0 to 4096Ts and a frequency range of 0 to 200Hz. m=9 is the time section width, and k=3 is the number of detected targets. In the range of 0 to 4096Ts, one section is created every mTs, and the k largest Doppler amplitude data are searched within this section, and the distance T value is recorded. Then, the corresponding angle value is determined according to 4. The above is the sensing result of the distance and angle at the 1sth second.

[0118] Drawing the trajectory: The above steps are repeated to obtain the sensing results for 1 minute, and the trajectory is drawn as shown in Figure 23. The trajectory diagram clearly shows the drone trajectory A and two interference areas, where area B is the far leaf interference area and area C is the nearby fan interference area.

[0119] Hereinafter, based on the target sensing method based on the section trajectory according to any of the above embodiments, various embodiments of a communication device, a computer-readable storage medium, and a computer program product according to the embodiments of the present application are proposed.

[0120] Fig. 24 is a schematic diagram of a communication device according to an embodiment of the present application. As shown in Fig. 24, this communication device 200 includes a memory 210 and a processor 220. The number of memories 210 and processors 220 may be one or more, but Fig. 24 illustrates one memory 210 and one processor 220. The memory 210 and processor 220 of the device may be connected via a bus or in another manner, but Fig. 24 illustrates a connection via a bus.

[0121] The memory 210 can be used as a computer-readable storage medium to store software programs, computer-executable programs, and modules, such as program instructions / modules, corresponding to the target sensing method based on the segment trajectory according to any embodiment of the present application. The processor 220 executes the software programs, instructions, and modules stored in the memory 210 to realize the target sensing method based on the segment trajectory.

[0122] The memory 210 may mainly include a program storage area that may store an operating system, an application required for at least one function, and a data storage area. In addition, the memory 210 may include a high-speed random access memory, and may include non-volatile memory such as at least one magnetic disk memory device, a flash memory device, or other non-transitory solid-state storage device. In some examples, the memory 210 may include memories located remotely to the processor 220, and these remote memories may be connected to the device through a network. Examples of the above networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0123] An embodiment of the present application further provides a computer-readable storage medium having stored thereon computer-executable instructions for performing a segment trajectory based target sensing method according to any embodiment of the present application.

[0124] One embodiment of the present application further provides a computer program product including a computer program or computer instructions stored in a computer-readable storage medium, wherein a processor of the computer device reads the computer program or computer instructions from the computer-readable storage medium, and the processor executes the computer program or computer instructions, thereby causing the computer device to perform a target sensing method based on a segment trajectory according to any embodiment of the present application.

[0125] The system architecture and application scenarios described in the embodiments of the present application are intended to more clearly explain the technical solutions of the embodiments of the present application, and are not intended to limit the technical solutions of the embodiments of the present application. The technical solutions of the embodiments of the present application are equally applicable to similar technical modifications that accompany the evolution of system architecture and the emergence of new application scenarios.

[0126] All or some of the steps of the methods disclosed above, the systems, and the functional modules / units in the devices may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0127] In hardware embodiments, the division between functional modules / units mentioned in the above description does not necessarily correspond to a division of physical components. For example, one physical component may have multiple functions, and one function or step may be performed by multiple physical components in cooperation. Some or all of the physical components may be implemented as software executed by a processor, such as a central processor, digital signal processor, microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on a computer readable medium, which may include computer storage media (or non-transitory media) and communication media (or transitory media). As known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (e.g., computer readable instructions, data structures, program modules, or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cartridges, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and that can be accessed by a computer. Additionally, those skilled in the art will recognize that communication media typically include computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transmission mechanism and may include any information delivery media.

[0128] In this specification, terms such as "component", "module", "system" and the like are used to represent computer-related entities, hardware, firmware, a combination of hardware and software, software, or software in execution. For example, but not limited to, a component may be a process running on a processor, a processor, an object, an executable file, a thread of execution, a program, or a computer. By way of illustration, both an application running on a computing device and the computing device may be a component. One or more components may reside within a process or thread of execution, and the components may be located on one computer or distributed among two or more computers. Furthermore, these components may execute from various computer readable media having various data structures stored thereon. The components may communicate, for example, via local or remote processes, by signals having one or more data packets (e.g., data from two components interacting with other components across a local system, distributed system, or network, e.g., the Internet interacting with other systems via signals).

Claims

1. A target sensing method based on a segment trajectory, comprising: Calculating a delay Doppler spectrum of a received signal for each sensing signal period to obtain an overall delay Doppler spectrum of each received signal including all target information, the overall delay Doppler spectrum including angle information; partitioning the total delay Doppler spectrum and preferentially selecting and extracting the angle information to obtain a delay angle of arrival spectrum of the preferred multi-targets of the partition; determining a movement trajectory according to the timing sequence of the delay arrival angle spectrum of the priority multi-targets of the section; determining a moving target according to the movement trajectory.

2. The step of calculating a delay Doppler spectrum of a received signal received for each sensing signal period and obtaining a comprehensive delay Doppler spectrum of each of the received signals including all target information, Calculating a channel impulse response of a received signal for each sensing signal period received by each antenna to obtain a channel impulse response vector corresponding to each antenna; and calculating a delay-Doppler spectrum of all the channel impulse response vectors corresponding to all the antennas to obtain a total delay-Doppler spectrum of each of the received signals containing all target information.

3. said step of calculating delay-Doppler spectra of all said channel impulse response vectors corresponding to all said antennas to obtain a total delay-Doppler spectrum of each said received signal including all target information, said step comprising: calculating a delay Doppler spectrum of the channel impulse response vector corresponding to each of the antennas to obtain an initial delay Doppler spectrum including all target information corresponding to each of the antennas; and performing directional filtering on all of the initial delay-Doppler spectra corresponding to all of the antennas to obtain a total delay-Doppler spectrum of each of the received signals containing all target information.

4. The step of calculating a channel impulse response of a received signal for each sensing signal period received by each antenna and obtaining a channel impulse response vector corresponding to each antenna includes: Sampling each of the received signals received by each of the antennas based on a preset sampling period to obtain a plurality of sampling data; and obtaining, for each sensing signal period, a channel impulse response vector corresponding to each of the antennas based on a plurality of the sampling data corresponding to each of the antennas and a sensing signal transmitted within the sensing signal period.

5. said step of performing directional filtering on all of said initial delay Doppler spectra corresponding to all of said antennas to obtain a total delay Doppler spectrum of each of said received signals including all of said target information, acquiring a plurality of pieces of angle information; calculating a composite delay Doppler spectrum at an angle corresponding to the angle information for the initial delay Doppler spectra of all the antennas for each sensing signal period; and screening based on the composite delay Doppler spectrum of all of the sensing signal periods to obtain a comprehensive delay Doppler spectrum including all target information within the sensing signal periods.

6. The method according to claim 5 , wherein each delay Doppler spectrum binary data in the comprehensive delay Doppler spectrum is a delay Doppler spectrum binary data having a largest corresponding amplitude in a composite delay Doppler spectrum corresponding to all angles.

7. The step of partitioning the total delay Doppler spectrum and preferentially selecting and extracting the angle information to obtain a delay angle of arrival spectrum of the prioritized multi-targets of the partition includes: partitioning the total delay Doppler spectrum to obtain a plurality of partitions each including a plurality of delay Doppler spectrum binary data; a step of preferentially selecting a priority delay Doppler spectrum binary data corresponding to each of the sections from among all the delay Doppler spectrum binary data corresponding to each of the sections according to the number of targets; 2. The method of claim 1, further comprising: extracting the angle information for all priority delayed Doppler spectrum binary data in each of the sections to obtain a delayed arrival angle spectrum of priority multi-targets in each of the sections, wherein each of the priority delayed Doppler spectrum binary data corresponds to one priority target.

8. The step of preferentially selecting priority delay Doppler spectrum binary data corresponding to each of the sections from among all the delay Doppler spectrum binary data corresponding to each of the sections according to the number of targets includes: Sorting the amplitudes of all the delayed Doppler spectrum binary data corresponding to each of the sections in a descending or ascending order of values; and selecting the sorted delayed Doppler spectrum binary data corresponding to each of the sections in descending order of priority according to the number of targets to obtain prioritized delayed Doppler spectrum binary data corresponding to each of the sections.

9. The step of determining a movement trajectory according to the timing sequence of the delay arrival angle spectrum of the priority multi-targets of the section includes: determining a timing sequence of all of the delayed arrival angle spectra based on a plurality of the sensing signal periods; and performing curve fitting on all the delayed angle of arrival spectra according to the timing sequence to obtain at least one movement trajectory.

10. After the step of determining a moving target according to the movement trajectory, determining an inertial movement tendency of the moving target according to the movement trajectory; The method of claim 1 , further comprising: determining position information of the moving target based on the inertial moving tendency and the delayed arrival angle spectrum of prioritized multi-targets of the section corresponding to the next sensing signal period.

11. After the step of obtaining at least one movement trajectory, The method according to claim 9, further comprising the step of determining that a target is an interfering target when a relative position change of a prioritized multi-target after partitioning is smaller than a preset threshold value in a plurality of the integrated delayed Doppler spectra.

12. At least one processor; at least one memory storing at least one program; A communications device, wherein at least one of the programs, when executed by at least one of the processors, performs the segment trajectory based target sensing method according to any one of claims 1 to 11.

13. A computer-readable storage medium storing a processor-executable program which, when executed by a processor, executes the target sensing method based on the section trajectory according to any one of claims 1 to 11.

14. A computer program product including a computer program or computer instructions stored in a computer-readable storage medium, wherein a processor of a computer device reads the computer program or computer instructions from the computer-readable storage medium and executes the computer program or computer instructions to cause the computer device to perform a target sensing method based on a section trajectory described in any one of claims 1 to 11.

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