Target detection method and device of binary phase modulation radar and electronic equipment

Abstract

This application provides a target detection method, apparatus, and electronic device for binary phase-modulated radar, relating to the field of radar detection technology. The method is applied to a radar detection system. The radar detection system includes multiple transmitting antennas and multiple receiving antennas, forming a virtual array of elements arranged virtually, with a first virtual element overlapping a second virtual element. The method includes: controlling each transmitting antenna to simultaneously transmit detection signals and controlling each receiving antenna to receive echo signals; determining, based on each echo signal, a virtual element order that minimizes the phase difference between the first and second virtual elements, the virtual element order representing the correspondence between each echo signal and each virtual element; and calculating the angle of each existing target based on the determined virtual element order and the echo signals received by each receiving antenna. Applying this application can improve the accuracy of target detection.

Description

Technical Field

[0001] This application relates to the field of radar detection technology, and in particular to target detection methods, devices and electronic equipment for binary phase-modulated radar. Background Technology

[0002] Traffic flow monitoring is a crucial component of modern urban roads, highways, and intelligent transportation systems. It typically employs traffic radar to detect multiple targets within its coverage area around the clock, enabling the perception of traffic conditions such as vehicle flow and parking queues, as well as the detection of behaviors like speeding and driving in the wrong direction. Most traffic radars are MIMO (Multiple Input Multiple Output) radars with multiple transmitting and receiving antennas. The millimeter-level electromagnetic waves emitted by the radar's radio frequency system are reflected by the target, generating echo signals. By capturing these echo signals, the radar signal processing system can determine information such as the target's distance, angle, Doppler velocity, signal-to-noise ratio, and trajectory; this process is called target detection.

[0003] In related technologies, traffic radar typically uses TDM-MIMO (Time Division Multiplexing-Multiple-Input-Multiple-Output) for traffic flow monitoring. However, TDM-MIMO radar only has one transmission channel operating at a time, resulting in power loss and limited detection range. Therefore, improving the detection range of MIMO radar has become an urgent technical problem to be solved. Summary of the Invention

[0004] The purpose of this application is to provide a target detection method, apparatus, and electronic device for binary phase modulation radar to improve the detection range of MIMO radar. The specific technical solution is as follows:

[0005] A first aspect of this application provides a target detection method for a binary phase-modulated radar, applied to a radar detection system. The radar detection system includes multiple transmitting antennas and multiple receiving antennas, which form a virtual array element arranged virtually. A first virtual array element formed by a first transmitting antenna and a second receiving antenna overlaps with a second virtual array element formed by a second transmitting antenna and the first receiving antenna. The method includes:

[0006] The transmitting antennas are controlled to simultaneously transmit detection signals, and the receiving antennas are controlled to receive echo signals.

[0007] Based on each echo signal, determine the virtual array element order that minimizes the phase difference between the first virtual array element and the second virtual array element, wherein the virtual array element order is used to represent the correspondence between each echo signal and each virtual array element.

[0008] Based on the determined virtual array element order and the echo signals received by each of the receiving antennas, the angles of each existing detection target are calculated.

[0009] In one possible implementation, determining the virtual array element order that minimizes the phase difference between the first virtual array element and the second virtual array element based on each of the echo signals includes:

[0010] Extract the first phase of the first echo signal received by the first receiving antenna and the second phase of the second echo signal, and extract the third phase of the first echo signal received by the second receiving antenna and the fourth phase of the second echo signal; wherein, the first echo signal is the signal transmitted by one of the first transmitting antenna and the second transmitting antenna, and the second echo signal is the signal transmitted by the other;

[0011] Calculate the first difference between the second phase and the third phase, and the second difference between the first phase and the fourth phase, and compare the relative magnitudes of the first difference and the second difference.

[0012] Based on the relative size, the echo signals corresponding to the first virtual array element and the second virtual array element are determined, and the virtual array element sorting is obtained.

[0013] In one possible implementation, the echo signals corresponding to the first virtual array element and the second virtual array element are determined based on their relative magnitudes:

[0014] If the first difference is less than the second difference, the first echo signal received by the first receiving antenna is determined as the echo signal corresponding to the second virtual array element, and the second echo signal received by the second receiving antenna is determined as the echo signal corresponding to the first virtual array element.

[0015] If the second difference is less than the first difference, the second echo signal received by the first receiving antenna is determined as the echo signal corresponding to the second virtual array element, and the first echo signal received by the second receiving antenna is determined as the echo signal corresponding to the first virtual array element.

[0016] In one possible embodiment, calculating the angle of each existing detection target based on the determined virtual array element order and the echo signals received by each of the receiving antennas includes:

[0017] Based on the determined virtual array element order and the echo signals received by each of the receiving antennas, the distance, ambiguity velocity and angle of each detected target in the first data frame and the second data frame are calculated.

[0018] The method further includes:

[0019] Based on the distance and the angle, identify the same detection target among the detection targets as the detection target to be solved;

[0020] Based on the fuzzy velocity of the target to be detected in the first data frame and the second data frame, candidate values ​​of the true velocity of the target to be detected in the first data frame and candidate values ​​of the true velocity in the second data frame are determined.

[0021] The candidate value that minimizes the difference in the true velocity of the target in the first data frame and the second data frame is calculated and taken as the true velocity of the target in the second data frame.

[0022] In one possible implementation, the method further includes:

[0023] The distance, fuzzy velocity, and angle of each detected target are obtained in the third data frame acquired by the binary phase-modulated radar, wherein the third data frame is after the second data frame;

[0024] Based on the distance and the angle, the target to be detected is determined in the third data frame;

[0025] Based on the ambiguous velocity of the target to be detected in the third data frame, determine the candidate values ​​of the true velocity of the target to be detected in the third data frame;

[0026] The candidate value that minimizes the difference between the true velocity of the target in the third data frame and the true velocity in the second data frame is calculated and taken as the true velocity of the target in the third data frame.

[0027] In one possible implementation, the candidate values ​​for the true velocity of the target to be detected are determined as follows:

[0028] v r =m×v max +v a

[0029] Among them, v r Here are candidate values ​​for the actual speed, m is the preset fuzzy number, and v is the value for the speed. max To preset the maximum unambiguous speed, v aLet be the fuzzy velocity of the target to be detected.

[0030] In one possible implementation, determining the same detection target among the detection targets based on the distance and the angle includes:

[0031] Based on the distance and the angle, determine the first position of each first detection target in the first data frame and the second position of each second detection target in the second data frame;

[0032] For any first detection target in the first data frame, calculate the difference between the first position of the first detection target and the second position of each second detection target in the second data frame; if the difference between the position of the first detection target and the second detection target is less than a preset position threshold, then the first detection target and the second detection target are determined to be the same detection target;

[0033] The preset location threshold is obtained by weighted summation of the probability of the detected target belonging to each category and the distance threshold set for each category. The distance threshold set for each category is positively correlated with the size of the target in that category.

[0034] The method includes:

[0035] The trajectory of each of the aforementioned detection targets is determined based on their distance, angle, and actual speed at different times.

[0036] A second aspect of this application provides a target detection device for a binary phase-modulation radar, applied to a radar detection system. The radar detection system includes multiple transmitting antennas and multiple receiving antennas, which form a virtual array element arranged virtually. A first virtual array element formed by a first transmitting antenna and a second receiving antenna overlaps with a second virtual array element formed by a second transmitting antenna and the first receiving antenna. The device includes:

[0037] The antenna control module is used to control each of the transmitting antennas to transmit detection signals simultaneously and to control each of the receiving antennas to receive echo signals.

[0038] The sorting determination module is used to determine the virtual array element sorting that minimizes the phase difference between the first virtual array element and the second virtual array element based on each echo signal, wherein the virtual array element sorting is used to represent the correspondence between each echo signal and each virtual array element.

[0039] An angle calculation module is used to calculate the angle of each existing detection target based on the determined virtual array element order and the echo signals received by each of the receiving antennas.

[0040] A third aspect of this application provides an electronic device, including:

[0041] Memory, used to store computer programs;

[0042] The processor, when executing a program stored in memory, implements any of the aforementioned binary phase-modulation radar target detection methods.

[0043] In a fourth aspect of this application, a computer-readable storage medium is provided, wherein a computer program is stored therein, and when executed by a processor, the computer program implements the target detection method of any of the aforementioned binary phase modulation radars.

[0044] The target detection method, apparatus, and electronic equipment of the binary phase-modulated radar provided in this application have overlapping first virtual array elements formed by the first transmitting antenna and the second receiving antenna of the radar detection system, making it impossible to directly distinguish the correspondence between the echo signals received by the first receiving antenna and the echo signals received by the second receiving antenna and the first and second virtual array elements. However, when the phases of the overlapping array elements are close and the phase difference between the first and second virtual array elements is minimized, the correspondence between the echo signals received by the first receiving antenna and the echo signals received by the second receiving antenna and the first and second virtual array elements can be determined. That is, the correspondence between all echo signals and all virtual array elements can be determined. Then, the angle of each detected target can be accurately calculated based on this correspondence and each echo signal. By minimizing the phase difference of the overlapping array elements, the signal-to-noise ratio is improved, thereby increasing the detection range of the MIMO radar.

[0045] Of course, implementing any product or method of this application does not necessarily require achieving all of the advantages described above at the same time. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other embodiments can be obtained based on these drawings.

[0047] Figure 1 This is a structural example diagram of the radar detection system provided in the embodiments of this application;

[0048] Figure 2 A first schematic diagram of a target detection method for binary phase-modulated radar provided in an embodiment of this application;

[0049] Figure 3aAn example diagram of the first type of transmission waveform provided in the embodiments of this application;

[0050] Figure 3b An example diagram of the second type of transmission waveform provided in the embodiments of this application;

[0051] Figure 3c An example diagram of the third type of transmission waveform provided in the embodiments of this application;

[0052] Figure 4 Example diagram of the range-Doppler velocity spectrum provided in the embodiments of this application;

[0053] Figure 5 Example diagram of virtual array element sorting provided in the embodiments of this application;

[0054] Figure 6 Example image of the results of three-dimensional fast Fourier transform;

[0055] Figure 7 A second schematic diagram of a target detection method for binary phase-modulated radar provided in an embodiment of this application;

[0056] Figure 8 Example diagram of phase-channel correspondence provided in the embodiments of this application;

[0057] Figure 9 A third schematic diagram of a target detection method for binary phase-modulated radar provided in an embodiment of this application;

[0058] Figure 10 A fourth schematic diagram of a target detection method for binary phase-modulated radar provided in an embodiment of this application;

[0059] Figure 11 A fifth schematic diagram of a target detection method for binary phase-modulated radar provided in the embodiments of this application;

[0060] Figure 12 Example diagrams showing the radar measurement range at different times provided in the embodiments of this application;

[0061] Figure 13 A sixth schematic diagram of a target detection method for binary phase-modulated radar provided in the embodiments of this application;

[0062] Figure 14 A seventh schematic diagram of a target detection method for binary phase-modulated radar provided in the embodiments of this application;

[0063] Figure 15 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0064] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art based on this application are within the scope of protection of this application.

[0065] First, the technical terms used in the embodiments of this application will be explained:

[0066] Overlapping elements: In this article, this refers to array elements that overlap. By overlapping the elements, the effective aperture of the array can be increased, thereby improving resolution, and the effective receiving area of ​​the array can also be increased, thus improving the signal-to-noise ratio.

[0067] When using BPM-MIMO radar for target detection, binary phase modulation is applied to different transmitting antennas in the slow time dimension to achieve synchronous radiation of waveform signals from M transmitting antennas. However, due to the constraints of phase modulation coding, the pulse repetition time interval of the chirped signal is effectively extended to M times its original value, resulting in a reduction of the ambiguity velocity measurement range to 1 / M of its original value. Therefore, BPM-MIMO radar is typically used in scenarios involving stationary or low-speed targets. When applied to high-speed target detection scenarios, a de-ambiguity velocity algorithm needs to be introduced to increase the radar's velocity measurement range to meet the requirements of high-speed target detection.

[0068] Traditional track deblurring algorithms determine the true speed of a target by calculating the rate of change of target distance over a period of time. This type of algorithm has two problems: 1. When a large target approaches the radar blind zone, the distance change will be inaccurate, which will cause the deblurring speed algorithm to fail; 2. The blind speed range exists in all radars. When the true speed is close to the blind speed, the ground clutter will affect the target and make it impossible to detect it effectively.

[0069] To improve the detection range of MIMO radar, a first aspect of this application provides a target detection method for binary phase-modulated radar, applied to a radar detection system. The radar detection system includes multiple transmitting antennas and multiple receiving antennas, which form a virtual array of elements arranged virtually. The first virtual array formed by a first transmitting antenna and a second receiving antenna overlaps with a second virtual array formed by a second transmitting antenna and a first receiving antenna. To ensure this overlap, the phase centers of the first and second virtual arrays coincide, meaning the sum of the position vectors of the first transmitting antenna and the second receiving antenna is equal to the sum of the position vectors of the second transmitting antenna and the first receiving antenna.

[0070] Understandably, due to possible errors in actual operation, the distance between the phase centers of the first virtual array element and the second virtual array element may not completely coincide, but the distance between the phase centers may be less than a preset threshold. In this case, the first virtual array element and the second virtual array element may also be considered to overlap.

[0071] The receiving antenna also includes a third receiving antenna in addition to the first and second receiving antennas. There can be one or more third receiving antennas.

[0072] For example, such as Figure 1 The diagram shown is an example of the structure of a radar detection system provided in this application embodiment. The radar detection system includes two transmitting antennas and eight receiving antennas, namely, a first transmitting antenna 11, a second transmitting antenna 12, a first receiving antenna 21, a second receiving antenna 22, a third receiving antenna 23, a fourth receiving antenna 24, a fifth receiving antenna 25, a sixth receiving antenna 26, a seventh receiving antenna 27, and an eighth receiving antenna 28. The positions of the first and second transmitting antennas are [0; 10.5] × λ, and the positions of the first to eighth receiving antennas are [0; 2.5; 4; 6; 7; 8; 9; 10.5] × λ. It can be seen that the virtual array element formed by the first transmitting antenna 11 and the eighth receiving antenna 28 overlaps with the virtual array element formed by the second transmitting antenna 12 and the second receiving antenna 21.

[0073] like Figure 2 The diagram shown is a first schematic representation of a target detection method for a binary phase-modulation radar provided in this application. The method includes the following steps:

[0074] Step S10: Control each transmitting antenna to simultaneously transmit detection signals and control each receiving antenna to receive echo signals.

[0075] Step S20: Based on each echo signal, determine the order of virtual array elements that minimizes the phase difference between the first virtual array element and the second virtual array element.

[0076] Among them, the virtual array element sorting is used to represent the correspondence between each echo signal and each virtual array element;

[0077] Step S30: Based on the determined virtual array element order and the echo signals received by each receiving antenna, calculate the angle of each existing detection target.

[0078] In the embodiments of this application, the first virtual array element formed by the first transmitting antenna and the second receiving antenna of the radar detection system overlaps with the second virtual array element formed by the first transmitting antenna and the first receiving antenna. Therefore, it is impossible to directly distinguish the correspondence between the echo signals received by the first receiving antenna and the echo signals received by the second receiving antenna and the first and second virtual array elements. However, when the phases of the overlapping array elements are close, and the phase difference between the first and second virtual array elements is minimized, the correspondence between the echo signals received by the first and second receiving antennas and the first and second virtual array elements can be determined. That is, the correspondence between all echo signals and all virtual array elements can be determined. Furthermore, the angle of each detected target can be accurately calculated based on this correspondence and each echo signal. By minimizing the phase difference of the overlapping array elements, the signal-to-noise ratio is improved, thereby increasing the detection range of the MIMO radar.

[0079] The following is a detailed explanation of steps S10 to S30:

[0080] In step S10 above, the detection signal refers to the electromagnetic wave emitted by the transmitting antenna for detecting the target. The waveform signal is the time-domain representation of the detection signal. Controlling each transmitting antenna to simultaneously emit the detection signal means performing binary phase modulation on different transmitting antennas to achieve synchronous radiation of the waveform signals from each transmitting antenna. Figure 1 Taking the radar detection system shown as an example, the modulation phase of the first transmitting antenna 11 is [0; 0; ...; 0; 0], and the modulation phase of the second transmitting antenna 12 is [0; π; ...; 0; π].

[0081] When the transmitting antenna transmits electromagnetic waves, the transmitted waveforms of consecutive frames cycle according to a preset rule. For example, the transmitted waveforms of consecutive frames cycle according to [transmitted waveform 1; transmitted waveform 2; transmitted waveform 3; ...; transmitted waveform 1; transmitted waveform 2; transmitted waveform 3]. Figure 3a The diagram shown is an example of the first type of transmission waveform provided in this application embodiment. Figure 3b The diagram shown is an example of the second type of transmission waveform provided in this application embodiment. Figure 3c The diagram shown is an example of a third type of transmission waveform provided in this application embodiment. The only difference between the different transmission waveforms is the idle time. Figure 3a , Figure 3b , Figure 3c Idle time 1, idle time 2, and idle time 3 are different. According to the speed measurement range formula (1), different idle times will lead to different chirp repetition periods, and therefore the speed measurement range of the radar continuous frames will also be different:

[0082]

[0083] Where λ is the wavelength, v max The maximum unambiguous velocity, i.e., the maximum velocity measurement range, is represented by T, which is the chirp repetition period. For example, taking a 92GHz radar as an example, the repetition period and velocity measurement range corresponding to different idle times are shown in Table 1 below.

[0084] Table 1. Correspondence between repetition period and speed measurement range for idle time.

[0085] 92GHz 3.26mm 4us 31us 94.67km / h 92GHz 3.26mm 6us 33us 88.93km / h 92GHz 3.26mm 8us 35us 83.85km / h

[0086] Electromagnetic waves emitted by a transmitting antenna are reflected back after encountering a target object, forming an echo signal. Different receiving antennas use different receiving channels to receive these echo signals. Each receiving channel contains mixed echo signals from various transmitting antennas. Due to phase modulation of the transmitting antennas, the receiving antennas can separate the mixed echo signals in the receiving channel based on the phase difference, thus distinguishing the signal sources of each echo signal within the mixed echo signal. However, because the phase centers of overlapping array elements coincide, it is not possible to directly distinguish the signal sources of each echo signal based on the phase difference for overlapping array elements. For example, after receiving each echo signal, a two-dimensional fast Fourier transform can be performed on the echo signals received by each receiving channel to obtain the results corresponding to each receiving channel. Then, the results corresponding to each receiving channel are non-coherently accumulated to obtain the range-Doppler velocity spectrum. Finally, the range cell and fuzzy velocity cell of the target are obtained using a constant false alarm rate (CFAR) algorithm. Figure 4 The diagram shown is an example of a range-Doppler velocity spectrum provided in an embodiment of this application. The positions of range index 58, velocity index 51, and range index 58, velocity index 307 are related to the spectral "shift" caused by the alternating periodic changes of the transmitted signal. The relative velocity index difference between the two peaks is fixed, but the overall difference changes with the relative velocity to the target. Therefore, it is impossible to distinguish the phase relationship between the two transmitted signals, i.e., it is impossible to distinguish between the two transmitting antennas.

[0087] Still with Figure 1 Taking the radar detection system shown as an example, the virtual array element formed by the first transmitting antenna 11 and the eighth receiving antenna 28 overlaps with the virtual array element formed by the second transmitting antenna 12 and the first receiving antenna 21. The first receiving antenna 21 receives the echo signal transmitted by the first transmitting antenna 11 and the echo signal transmitted by the second transmitting antenna 12. The eighth receiving antenna 28 receives the echo signal transmitted by the first transmitting antenna 11 and the echo signal transmitted by the second transmitting antenna 12. It is impossible to determine which echo signal was transmitted by the first transmitting antenna 11 and which echo signal was transmitted by the second transmitting antenna 12.

[0088] Understandably, in related technologies, angle measurement in radar angle measurement is performed according to the following steps:

[0089] First, extract the echo signals received by each receiving antenna and determine the correspondence between each echo signal and each virtual array element.

[0090] Then, phase extraction is performed on each receiving channel according to the following formula (1):

[0091]

[0092] Among them, s[m t ,m r Let f0 be the phase of the echo signal corresponding to the virtual array element formed by the t-th transmitting antenna and the r-th receiving antenna, c be the speed of light, f0 be the frequency band, α be the angle corresponding to the detected target, and d be the phase of the echo signal. t [m t ] represents the position of the t-th transmitting antenna, d r [m r [ ] represents the position of the r-th receiving antenna.

[0093] Finally, based on the phase of each receiving channel, the angle α corresponding to the detected target can be calculated, thus completing the angle resolution.

[0094] However, due to the existence of overlapping array elements in the virtual array of this application, Figure 1 Taking a radar detection system as an example, assuming that the signal source of each echo signal of the overlapping array element can be determined, the phase s of the echo signals transmitted by the first transmitting antenna 11 and received by the eighth receiving antenna 28 are calculated according to the above formula (2) [1]. t 8 r The phase s[2] of the echo signal transmitted by the second transmitting antenna 12 and received by the first receiving antenna 21 t ,1 r ]:

[0095]

[0096] It is evident that the phases of overlapping array elements are the same or nearly the same at any angle or velocity. For example... Figure 5 The figure shown is an example diagram of the virtual array element sorting provided in the embodiment of this application. As can be seen from the figure, the positions of the virtual array elements constituting the overlapping array elements coincide, and thus it is impossible to distinguish the correspondence between each virtual array element constituting the overlapping array elements and the echo signal. In other words, it is impossible to distinguish the phase of the receiving channel corresponding to the virtual array elements constituting the overlapping array elements, and therefore it is impossible to perform angle resolution calculation.

[0097] Since the phases of the two virtual array elements that constitute an overlapping array element are the same or almost the same, while the phase difference between the two virtual array elements that do not constitute an overlapping array element is large, the virtual array element order that minimizes the phase difference between the first virtual array element and the second virtual array element can be determined through the above step S20.

[0098] For example, assuming the echo signals received by the first receiving antenna are echo signal 1 and echo signal 2, and the echo signals received by the second receiving antenna are echo signal 3 and echo signal 4, if echo signal 1 is transmitted by the second transmitting antenna, echo signal 2 is transmitted by the first transmitting antenna, echo signal 3 is transmitted by the first transmitting antenna, and echo signal 4 is transmitted by the second transmitting antenna, then the phase difference between the first virtual array element and the second virtual array element is the smallest, and it can be determined that the first virtual array element corresponds to echo signal 3 and the second virtual array element corresponds to echo signal 1.

[0099] After determining the order of the virtual array elements constituting the overlapping array elements, the correspondence between each virtual array element and each echo signal can be obtained, i.e., the virtual array element order. Then, the angle of the detected target can be calculated through step S30. In step S30 above, three-dimensional fast Fourier transform can be used to complete the angle determination, or other methods can be used; this application embodiment does not limit this. Figure 6 The image shown is an example of the result of a 3D Fast Fourier Transform (FFT). After performing the FFT, point cloud data of the target can be obtained, including distance, Doppler velocity (i.e., blur velocity in the following text), and angle. Figure 6 It is known that the horizontal angular resolution of the binary phase-modulated radar provided in this application embodiment is 2.6649°.

[0100] In one possible implementation, in step S20 above, determining the virtual array element order that minimizes the phase difference between the first virtual array element and the second virtual array element based on each echo signal can be achieved by inputting each echo signal into a pre-trained machine learning model, and having the model output the virtual array element order. During training, the machine learning model learns how to order the virtual array elements to minimize the phase difference between the first virtual array element and the second virtual array element.

[0101] In another possible implementation, the phase difference between each echo signal received by the first and second receiving antennas can be determined, and the virtual array element order can be determined based on the magnitude of the phase difference.

[0102] Based on this, such as Figure 7 The diagram shown is a second schematic of a target detection method for binary phase-modulated radar provided in this application embodiment. The method includes the following steps:

[0103] Step S10: Control each transmitting antenna to simultaneously transmit detection signals and control each receiving antenna to receive echo signals.

[0104] Step S201: Extract the first phase of the first echo signal received by the first receiving antenna and the second phase of the second echo signal, and extract the third phase of the first echo signal received by the second receiving antenna and the fourth phase of the second echo signal.

[0105] The first echo signal is a signal transmitted by one of the first transmitting antenna and the second transmitting antenna, and the second echo signal is a signal transmitted by the other.

[0106] Step S202: Calculate the first difference between the second phase and the third phase and the second difference between the first phase and the fourth phase, and compare the relative magnitudes of the first difference and the second difference.

[0107] Step S203: Based on the relative size, determine the echo signals corresponding to the first virtual array element and the second virtual array element respectively, and obtain the virtual array element sorting.

[0108] Step S30: Based on the determined virtual array element order and the echo signals received by each receiving antenna, calculate the angle of each existing detection target.

[0109] Steps S10 and 30 are described above and will not be repeated here. Steps 201 to S203 are detailed steps of step S20 above. The following is an explanation of steps S201 to S203.

[0110] In step S201 above, the phase of the echo signal received by each receiving antenna is extracted. This can be done by the aforementioned formula (1), by matched filtering + peak phase extraction, by Doppler processing, or by other methods. This application embodiment does not limit this method.

[0111] As can be seen from the above, the transmitting antenna in this application is subjected to binary phase modulation. Therefore, the phase of the first echo signal when it is a signal transmitted by the first transmitting antenna is different from the phase of the first echo signal when it is transmitted by the second transmitting antenna, and the phase of the second echo signal when it is transmitted by the first transmitting antenna is also different from the phase of the second echo signal when it is transmitted by the second transmitting antenna.

[0112] Therefore, in step S201 above, phase extraction is performed for the following scenarios: when the first echo signal is a signal transmitted by the first transmitting antenna, when the first echo signal is a signal transmitted by the second transmitting antenna, when the second echo signal is a signal transmitted by the first transmitting antenna, and when the second echo signal is a signal transmitted by the second transmitting antenna.

[0113] Still with Figure 1Taking a radar detection system with 2 transmitters and 8 receivers as an example, the extracted first phase is s[1] t 8 r ], representing the phase of the echo signal transmitted by the first transmitting antenna 11 and received by the eighth receiving antenna 28; the second phase is s[2 t 8 r ], representing the phase of the echo signal transmitted by the second transmitting antenna 12 and received by the eighth receiving antenna 28; the third phase is s[1 t ,1 r ], representing the phase of the echo signal transmitted by the first transmitting antenna 11 and received by the first receiving antenna 21; the fourth phase is s[2 t ,1 r [ ] represents the phase of the echo signal transmitted by the second transmitting antenna 12 and received by the first receiving antenna 21. The phase is calculated by extracting the virtual channels corresponding to the distance and velocity of the detected target, as shown below. Figure 8 As shown, Figure 8 This is an example diagram of the phase-channel correspondence provided in the embodiments of this application. In the diagram, solid lines represent channels ordered by order 0, and dashed lines represent channels ordered by order 1.

[0114] Then calculate the first difference between the second phase and the third phase. The second difference between the fourth phase and the fourth phase

[0115]

[0116] In step S203 above, the echo signals corresponding to the first virtual array element and the second virtual array element are determined according to their relative size to obtain the virtual array element sorting. This can be achieved by inputting the calculated relative size of the first difference and the second difference into a pre-trained model, and having the model output the virtual array element sorting. During the training process, the model learns how to sort the virtual array elements according to the relative size of the difference.

[0117] In the embodiments of this application, since the phases of the overlapping array elements are close, for the receiving antennas in the virtual array elements constituting the overlapping array elements, after extracting the phase of the echo signal received by the receiving antenna, the phase difference of different echo signals is calculated respectively. When the phase difference is the smallest, the correspondence between the echo signal received by the first receiving antenna, the echo signal received by the second receiving antenna and the first virtual array element and the second virtual array element can be determined. That is, the correspondence between all echo signals and all virtual array elements can be determined, and then the angle measurement can be completed.

[0118] As can be seen from the above, the phases of the two virtual array elements that constitute an overlapping array element are the same or almost the same, while the phase difference between the two virtual array elements that do not constitute an overlapping array element is large. Therefore, in another possible implementation, the signal source of the first echo signal and the second echo signal can be determined by determining the minimum value of the first difference and the second difference, and then the echo signal corresponding to the first virtual array element and the second virtual array element can be determined.

[0119] like Figure 9 The diagram shown is a third schematic of a target detection method for binary phase-modulated radar provided in this application. The method includes the following steps:

[0120] Step S10: Control each transmitting antenna to simultaneously transmit detection signals and control each receiving antenna to receive echo signals.

[0121] Step S201: Extract the first phase of the first echo signal received by the first receiving antenna and the second phase of the second echo signal, and extract the third phase of the first echo signal received by the second receiving antenna and the fourth phase of the second echo signal.

[0122] The first echo signal is a signal transmitted by one of the first transmitting antenna and the second transmitting antenna, and the second echo signal is a signal transmitted by the other.

[0123] Step S202: Calculate the first difference between the second phase and the third phase and the second difference between the first phase and the fourth phase, and compare the relative magnitudes of the first difference and the second difference.

[0124] Step S2031: If the first difference is less than the second difference, the first echo signal received by the first receiving antenna is determined as the echo signal corresponding to the second virtual array element, and the second echo signal received by the second receiving antenna is determined as the echo signal corresponding to the first virtual array element.

[0125] Step S2032: If the second difference is less than the first difference, the second echo signal received by the first receiving antenna is determined as the echo signal corresponding to the second virtual array element, and the first echo signal received by the second receiving antenna is determined as the echo signal corresponding to the first virtual array element.

[0126] Step S30: Based on the determined virtual array element order and the echo signals received by each receiving antenna, calculate the angle of each existing detection target.

[0127] Steps S10, S30, and S201-S202 are described above and will not be repeated here. Steps S2031-S2032 are... Figure 7 The detailed steps of step S203.

[0128] As mentioned above Figure 1 Taking the radar detection system shown as an example, if Then it is assumed that the first virtual array element is composed of the first transmitting antenna 11 and the eighth receiving antenna 28, and the second virtual array element is composed of the second transmitting antenna 12 and the first receiving antenna 21; if It is then assumed that the first virtual array element is composed of the second transmitting antenna 12 and the eighth receiving antenna 28, and the second virtual array element is composed of the first transmitting antenna 12 and the first receiving antenna 21. At that time, an error message will be sent.

[0129] Using the embodiments of this application, for the receiving antenna in the virtual array elements constituting the overlapping array elements, after extracting the phase of the echo signal received by the receiving antenna, the phase difference of different echo signals is calculated respectively. By comparing the phase differences of different echo signals, the correspondence between all echo signals and all virtual array elements can be accurately determined.

[0130] Understandably, for radar to accurately detect a target, it needs to determine not only the target's angle but also its speed and distance. However, as mentioned earlier, radar has a maximum unambiguous velocity v. max When the actual speed of the detected target exceeds v max The speed measurement will be folded to [-v] max ,v max Within this range, the velocity is ambiguous, making it impossible to determine the true velocity of the target and thus impossible to accurately detect the target. Based on this, a second aspect of this application provides a target detection method for binary phase-modulated radar, such as... Figure 10 The diagram shown is a fourth schematic of a target detection method for binary phase-modulated radar provided in this application. The method includes the following steps:

[0131] Step S100: Obtain the distance, fuzzy velocity, and angle of each detected target in the first and second data frames acquired by the binary phase modulation radar;

[0132] The angle is calculated using the target detection method of the binary phase-modulated radar described in the first aspect. The distance and fuzzy velocity of each detected target can be calculated during the target detection process using the binary phase-modulated radar described in the first aspect, or they can be obtained using existing radar ranging and velocity measurement methods. This application does not limit this.

[0133] Step S200: Based on distance and angle, identify the same detection target among all detection targets as the detection target to be solved;

[0134] Specifically, for each detected target in two adjacent frames, if the time interval between the first and second data frames is very small, it can be assumed that the position and angle of the same target do not change much within that time interval. Therefore, detected targets whose distance changes are less than a preset distance threshold and whose angle changes are less than a preset angle threshold are identified as the same detected target. For example, assuming that the position of detected target 1 in the first data frame is position 1 and its angle is angle 1, and the position of detected target 2 in the second data frame is position 2 and its angle is angle 1, and the time interval between the first and second data frames is less than a preset time threshold, if the difference between position 1 and position 2 is less than a preset distance threshold and the difference between angle 1 and angle 2 is less than a preset angle threshold, then detected target 1 and detected target 2 are the same detected target to be solved.

[0135] Step S300: Based on the fuzzy velocity of the target to be detected in the first data frame and the second data frame, determine the candidate values ​​of the true velocity of the target to be detected in the first data frame and the candidate values ​​of the true velocity in the second data frame.

[0136] Since the ambiguity velocity is caused by periodic aliasing due to Doppler frequency shift, and the ambiguity number reflects the number of such periodic aliasing events, multiple candidate values ​​for the true velocity of the target in the first data frame can be determined based on the ambiguity number and the ambiguity velocity of the target in the first data frame. For example, assuming the ambiguity velocity in the first data frame is x1 and the ambiguity number is {-1, 0, 1}, then the candidate values ​​for the true velocity are: -v max +x1, x1,v max +x1.

[0137] Step S400: Calculate the candidate value that minimizes the difference between the true velocity of the target in the first data frame and the second data frame, and use it as the true velocity of the target in the second data frame.

[0138] Understandably, the velocity change of the target to be detected should be small in a short period of time. Since the time interval between the first data frame and the second data frame is less than the preset time threshold, it can be assumed that the difference between the actual velocity of the target to be detected in the first data frame and the actual velocity in the second data frame should be the smallest.

[0139] For example, assuming the blurred velocity of the target to be detected in the first data frame is x1 with a blur number of {-1, 0, 1}, and the blurred velocity in the second data frame is x2 with a blur number of {-1, 0, 1}, then the candidate value for the true velocity of the target to be detected in the first data frame is: -v max +x1, x1,v max +x1, then the candidate values ​​for the true velocity in the second data frame are: -vmax +x2, x2,v max +x2, which involves subtracting each candidate value of the true velocity in the first data frame from a candidate value of the true velocity in the second data frame, and determining the true velocity of the target in the second data frame when the difference is minimized. For example, assume x1 and v max If the difference between +x2 is minimized, then the true velocity of the target to be detected in the first data frame is x1.

[0140] Using the embodiments of this application, it is possible to determine whether the detection targets at different times are the same detection target based on the angle and distance of each detection target. Since the true speed of the same detection target in the first data frame and the second data frame should be close, the true speed of the detection target in the second data frame can be determined based on the candidate value where the difference between the true speeds of the detection target in the first data frame and the second data frame is the smallest. This achieves accurate calculation of the true speed of the detection target and improves the accuracy of target detection.

[0141] The calculation of the target's true velocity in the second data frame was explained above. This same calculation method can also be used to calculate the target's true velocity in other data frames, such as... Figure 11 The diagram shown is a fifth illustration of a target detection method for binary phase-modulated radar provided in this application. The method includes the following steps:

[0142] Step S100: Obtain the distance, fuzzy velocity, and angle of each detected target in the first and second data frames acquired by the binary phase modulation radar;

[0143] Step S200: Based on distance and angle, identify the same detection target among all detection targets as the detection target to be solved;

[0144] Step S300: Based on the fuzzy velocity of the target to be detected in the first data frame and the second data frame, determine the candidate values ​​of the true velocity of the target to be detected in the first data frame and the candidate values ​​of the true velocity in the second data frame.

[0145] Step S400: Calculate the candidate value that minimizes the difference between the true velocity of the target in the first data frame and the second data frame, and use it as the true velocity of the target in the second data frame.

[0146] Step S500: Obtain the distance, fuzzy velocity, and angle of each detected target in the third data frame acquired by the binary phase modulation radar;

[0147] The third data frame is received after the second data frame, meaning that the reception time of the third data frame is later than the reception time of the second data frame.

[0148] Step S600: Determine the target to be detected in the third data frame based on the distance and angle;

[0149] Step S700: Based on the fuzzy velocity of the target to be detected in the third data frame, determine the candidate values ​​of the true velocity of the target to be detected in the third data frame.

[0150] Step S800: Calculate the candidate value that minimizes the difference between the true velocity of the target in the third data frame and the true velocity in the second data frame, and use it as the true velocity of the target in the third data frame.

[0151] Steps S100 to S400 are described above. Step S500 is similar to step S100, except that in step S500 the velocity is obtained in the third data frame, while in step S100 it is obtained in the first and second data frames. Step S600 is similar to step S200, step S700 is similar to step S300, and step S800 is similar to step S400, except that in step S400 the velocity in the second data frame is determined based on the candidate values ​​of the true velocity of the target in the first data frame and the candidate values ​​of the true velocity in the second data frame, while in step S800 the velocity in the third data frame is determined based on the true velocity of the target in the second data frame and the candidate values ​​of the true velocity in the third data frame. Steps S500 to S800 will not be described again here.

[0152] Using the embodiments of this application, since the true speed of the same detection target in adjacent data frames should be close, the true speed of the detection target in the third data frame can be determined by the candidate value where the difference between the true speed of the detection target in the second data frame and the true speed in the third data frame is the smallest, thus realizing the accurate calculation of the true speed of the detection target at any time.

[0153] Understandably, the difference between the positional differences of the same target in different data frames with a time interval of t and the distance the target travels at its actual speed over time t should be small. Figure 12 The diagram shows an example of the radar measurement range at different times provided in the embodiments of this application. The radar can measure the position of the vehicle at time T0 and the position of the vehicle at time T1 at the radar detection point shown in the diagram. If the size of the target to be detected is large, the calculated position difference of the target to be detected in different data frames with a time interval of t is inaccurate, and it is impossible to determine whether the target in the two data frames is the same target.

[0154] Based on this, in one possible implementation, such as Figure 13 The diagram shown is a sixth schematic of a target detection method for binary phase-modulated radar provided in this application. The method includes the following steps:

[0155] Step S100: Obtain the distance, fuzzy velocity, and angle of each detected target in the first and second data frames acquired by the binary phase modulation radar;

[0156] Step S2001: Determine the first position of each first detection target in the first data frame and the second position of each second detection target in the second data frame based on the distance and angle.

[0157] The position of each detection target can be calculated based on the distance and angle of the detection target in the data frame. In this case, the position is represented by the coordinates of the detection target in space, or by the distance and angle of the detection target in the data frame.

[0158] Step S2002: For any first detection target in the first data frame, calculate the difference between the first position of the first detection target and the second position of each second detection target in the second data frame; if the difference between the position of the first detection target and the position of the second detection target is less than a preset position threshold, then the first detection target and the second detection target are determined to be the same detection target.

[0159] The difference between the positions of the first and second detected targets is less than a preset position threshold, meaning that the difference between the positions of the first and second detected targets and the distance they move at the actual speed during the time interval between the first and second data frames is less than the preset position threshold. Specifically, whether the detected targets in each data frame are the same target can be determined using the following formula (7):

[0160] |(R last -R start )-v r ×t| <T r (7)

[0161] Among them, R start R represents the first position of the first detection target in the first data frame. last v represents the second position of the second detection target in the second data frame. r For true speed, T r This is a preset position threshold.

[0162] The preset location threshold is obtained by weighting and summing the probability of the detected target belonging to each category with a distance threshold set for each category. In one possible implementation, the categories are determined by the size of the detected target; the larger the size of the detected target, the larger the distance threshold set for its category. Specifically, the relationship between the preset location threshold and each category is as follows:

[0163] T r =∑P(x)×T x (8)

[0164] Where P(x) is the probability of classifying the detected target, and T x Distance thresholds are set for different categories. For example, assuming the target is a vehicle, the distance threshold is set to 10 meters for large vehicles, 5 meters for small vehicles, and 2 meters for non-motorized vehicles. The probability of detecting a large vehicle is 80%, a small vehicle is 15%, and a non-motorized vehicle is 5%. Then, the preset position threshold T... r =80%×10+15%×5+5%×2=8.85 meters.

[0165] By determining the distance threshold of the target category by the size of the detected target, and setting a preset position threshold based on the probability of the target category, the preset position threshold is made more reasonable. This reduces the possibility of misjudging the same detected target as different detected targets due to the large size of the detected target, and can accurately determine whether the detected targets in two data frames are the same target, thus improving the accuracy of target detection.

[0166] Step S300: Based on the fuzzy velocity of the target to be detected in the first data frame and the second data frame, determine the candidate values ​​of the true velocity of the target to be detected in the first data frame and the candidate values ​​of the true velocity in the second data frame.

[0167] Step S400: Calculate the candidate value that minimizes the difference between the true velocity of the target in the first data frame and the second data frame, and use it as the true velocity of the target in the second data frame.

[0168] By adopting the embodiments of this application, a preset position threshold is determined according to the probability of the detected target being of each category and the distance threshold set for each category. By comparing the difference between the first position of the first detected target in the first data frame and the second position of the second detected target in the second data frame with the preset position threshold, the possibility of misjudging the same detected target as different detected targets due to the large size of the detected target can be reduced, and the accuracy of determining the same detected target can be improved.

[0169] To avoid missing candidate values ​​for the true velocity, in one possible implementation, candidate values ​​for the true velocity of the target to be detected can be determined in the following manner:

[0170] v r =m×v max1 +v a1 (9)

[0171] Among them, v r Here are candidate values ​​for the actual speed, m is the preset fuzzy number, and v is the value for the speed. max To preset the maximum unambiguous speed, v a The ambiguity number is the velocity of the target to be detected. The ambiguity number can be determined by the multi-pulse repetition frequency method, or it can be set by the user based on experience and requirements, or it can be determined by other methods. This application embodiment does not limit this.

[0172] Understandably, according to Figure 3a , Figure 3b , Figure 3c It can be seen that the frequency changes with time, and the frequency change will inevitably cause the wavelength to change. According to formula (1) and figure, the maximum unambiguous speed is different for different wavelengths. That is to say, the maximum unambiguous speed is different at different times.

[0173] To more clearly illustrate the calculation process of the true velocity of the target to be detected in different data frames in the embodiments of this application, the following description is provided in conjunction with specific embodiments.

[0174] Assume there are y data frames of the target to be detected, where y ≥ 3.

[0175] For the first data frame containing the target to be solved, assume the ambiguity velocity of the target in the first data frame is v. a1 The maximum unambiguous speed corresponding to the first data frame is v. max1 If the ambiguity number is m1 = {-1, 0, 1}, then using formula (4), the candidate values ​​of the true velocity of the target to be solved in the first data frame can be determined as: v r11 =-v max1 +v a1 v r12 =v a1 v r13 =v max1 +v a1 ;

[0176] For the second data frame, assume the blur velocity of the target to be detected in the second data frame is v. a2 The maximum unambiguous velocity corresponding to the second data frame is v. max2If the fuzzy numbers are m2 = {-1, 0, 1}, then the fuzzy numbers m1 and m2 that minimize the difference are determined using the following formula:

[0177]

[0178] Assume that when m1 = 0 and m2 = 0, (m1 × v max1 +v a1 ) and (m2×v max2 +v a2 If the difference is minimized, then the true velocity v of the target in the second data frame can be calculated. r2 =0×v max2 +v a2 =v a2 .

[0179] For the data frames following the second data frame, referred to below as the third data frame, it is assumed that the blur velocity of the target to be detected in the third data frame is v. a3 The maximum unambiguous velocity corresponding to the second data frame is v. max3 The ambiguity number is m3 = {-1, 0, 1}, and the true velocity of the target to be detected can be calculated according to the following formula (11):

[0180]

[0181] Assume that when m3 = 1 (m3 × v max2 +v a3 ) and v r2 If the difference is minimized, the true velocity v of the target in the third data frame can be calculated. r3 =1×v max3 +v a3 .

[0182] Based on the aforementioned first and second aspects, after accurately acquiring the angle and velocity of the target, the target's trajectory can be determined. Therefore, in a third aspect of this application, a method for determining the target trajectory using a binary phase-modulation radar is provided, such as... Figure 14 The diagram shown is a seventh schematic of a target detection method for binary phase-modulated radar provided in this application. The method includes the following steps:

[0183] Step S1: Obtain the distance, true velocity, and angle of each detected target in the data frame acquired by the binary phase-modulated radar;

[0184] Wherein, the angle is calculated using the target detection method of the binary phase-modulated radar mentioned in the first aspect, and the actual speed is calculated using the target detection method of the binary phase-modulated radar mentioned in the second aspect.

[0185] Step S2: Determine the trajectory of each detection target based on its distance, angle, and actual speed at different times.

[0186] Step S1 is described in the first and second aspects above, and will not be repeated here.

[0187] In the embodiments of this application, the first virtual array element formed by the first transmitting antenna and the second receiving antenna of the radar detection system overlaps with the second virtual array element formed by the first transmitting antenna and the first receiving antenna. Therefore, it is impossible to directly distinguish the correspondence between the echo signals received by the first receiving antenna and the echo signals received by the second receiving antenna and the first and second virtual array elements. However, when the phases of the overlapping array elements are close, and the phase difference between the first and second virtual array elements is minimized, the correspondence between the echo signals received by the first and second receiving antennas and the first and second virtual array elements can be determined. That is, the correspondence between all echo signals and all virtual array elements can be determined. Furthermore, the angle of each detected target can be accurately calculated based on this correspondence and each echo signal. By minimizing the phase difference of the overlapping array elements, the signal-to-noise ratio is improved, thereby increasing the detection range of the MIMO radar. Furthermore, since the true velocities of the same target in adjacent data frames should be similar, the true velocity of the target in the third data frame can be determined by selecting the candidate value where the difference between the true velocity in the second and third data frames is minimized. This allows for accurate calculation of the target's true velocity at any given time. Thus, after accurately obtaining the target's angle and velocity, the target's trajectory can be precisely determined, improving the accuracy of the target's trajectory.

[0188] A fourth aspect of this application provides a binary phase-modulated radar angle measurement device applied to a radar detection system. The radar detection system includes multiple transmitting antennas and multiple receiving antennas, which form a virtual array element arranged virtually. A first virtual array element formed by a first transmitting antenna and a second receiving antenna overlaps with a second virtual array element formed by a second transmitting antenna and the first receiving antenna. The device includes:

[0189] The antenna control module is used to control each of the transmitting antennas to transmit detection signals simultaneously and to control each of the receiving antennas to receive echo signals.

[0190] The sorting determination module is used to determine the virtual array element sorting that minimizes the phase difference between the first virtual array element and the second virtual array element based on each echo signal, wherein the virtual array element sorting is used to represent the correspondence between each echo signal and each virtual array element.

[0191] An angle calculation module is used to calculate the angle of each existing detection target based on the determined virtual array element order and the echo signals received by each of the receiving antennas.

[0192] In one possible implementation, the sorting determination module determines the virtual array element sorting that minimizes the phase difference between the first virtual array element and the second virtual array element based on each of the echo signals. This includes: extracting a first phase of the first echo signal received by the first receiving antenna and a second phase of the second echo signal, and extracting a third phase of the first echo signal received by the second receiving antenna and a fourth phase of the second echo signal; wherein the first echo signal is a signal transmitted by one of the first transmitting antenna and the second transmitting antenna, and the second echo signal is a signal transmitted by the other; calculating a first difference between the second phase and the third phase and a second difference between the first phase and the fourth phase, and comparing the relative magnitudes of the first difference and the second difference; and determining the echo signals corresponding to the first virtual array element and the second virtual array element respectively based on the relative magnitudes to obtain the virtual array element sorting.

[0193] In one possible implementation, the sorting determination module determines the echo signals corresponding to the first virtual array element and the second virtual array element respectively based on the relative size, including: if the first difference is less than the second difference, determining the first echo signal received by the first receiving antenna as the echo signal corresponding to the second virtual array element, and determining the second echo signal received by the second receiving antenna as the echo signal corresponding to the first virtual array element; if the second difference is less than the first difference, determining the second echo signal received by the first receiving antenna as the echo signal corresponding to the second virtual array element, and determining the first echo signal received by the second receiving antenna as the echo signal corresponding to the first virtual array element.

[0194] In one possible implementation, the angle calculation module calculates the angle of each existing detection target based on the determined virtual array element order and the echo signals received by each of the receiving antennas, including: calculating the distance, fuzzy velocity, and angle of each detection target existing in the first data frame and the second data frame based on the determined virtual array element order and the echo signals received by each of the receiving antennas; the device further includes: a velocity determination module, used to determine candidate values ​​of the true velocity of the detection target in the first data frame and candidate values ​​of the true velocity in the second data frame based on the fuzzy velocity of the detection target in the first data frame and the second data frame; and a velocity calculation module, used to calculate the candidate value that minimizes the difference between the true velocities of the detection target in the first data frame and the second data frame, as the true velocity of the detection target in the second data frame.

[0195] In one possible implementation, the velocity calculation module is further configured to acquire the distance, ambiguous velocity, and angle of each detected target in the third data frame acquired by the binary phase-modulated radar, wherein the third data frame follows the second data frame; determine the detected target to be calculated in the third data frame based on the distance and the angle; determine candidate values ​​of the true velocity of the detected target in the third data frame based on the ambiguous velocity of the detected target in the third data frame; and calculate the candidate value that minimizes the difference between the true velocity of the detected target in the third data frame and the true velocity in the second data frame, and use this value as the true velocity of the detected target in the third data frame.

[0196] In one possible implementation, the candidate values ​​for the true velocity of the target to be detected are determined as follows:

[0197] v r =m×v max +v a

[0198] Among them, v r Here are candidate values ​​for the actual speed, m is the preset fuzzy number, and v is the value for the speed. max To preset the maximum unambiguous speed, v a Let be the fuzzy velocity of the target to be detected.

[0199] In one possible implementation, determining the same detection target among the detection targets based on the distance and the angle includes: determining the first position of each first detection target in the first data frame and the second position of each second detection target in the second data frame based on the distance and the angle; calculating the difference between the first position of the first detection target and the second position of each second detection target in the second data frame for any first detection target in the first data frame; if the difference between the position of the first detection target and the second detection target is less than a preset position threshold, then the first detection target and the second detection target are determined to be the same detection target; wherein the preset position threshold is obtained by weighted summation of the probability of the detection target belonging to each category and the distance threshold set for each category, and the distance threshold set for each category is positively correlated with the size of the target of each category.

[0200] In one possible implementation, the device further includes a trajectory determination module for determining the trajectory of each of the detection targets based on the distance, angle, and actual speed of each detection target at different times.

[0201] A third aspect of the embodiments of this application provides an electronic device, such as... Figure 15 As shown, it includes:

[0202] Memory 1501 is used to store computer programs;

[0203] The processor 1502, when executing the program stored in the memory 1501, implements the target detection method of the binary phase-modulated radar described in the first aspect above.

[0204] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0205] In an eighth aspect of the embodiments of this application, a computer-readable storage medium is also provided, wherein a computer program is stored therein, and when executed by a processor, the computer program implements the steps of the target detection method of the binary phase-modulated radar described in the first aspect.

[0206] In another embodiment provided in this application, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to execute any of the binary phase-modulation radar target detection methods described in the above embodiments.

[0207] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a solid-state drive (SSD), etc.

[0208] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0209] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the apparatus embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0210] The above description is merely a preferred embodiment of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application are included within the scope of protection of this application.

Claims

1. A target detection method for a binary phase-modulation radar, characterized in that, The method is applied to a radar detection system, which includes multiple transmitting antennas and multiple receiving antennas. The multiple transmitting antennas and multiple receiving antennas form a virtual array element arranged virtually, wherein a first virtual array element formed by a first transmitting antenna and a second receiving antenna overlaps with a second virtual array element formed by a second transmitting antenna and the first receiving antenna. Control each of the transmitting antennas to simultaneously transmit detection signals, and control each of the receiving antennas to receive echo signals; Based on each echo signal, determine the virtual array element order that minimizes the phase difference between the first virtual array element and the second virtual array element, wherein the virtual array element order is used to represent the correspondence between each echo signal and each virtual array element. Based on the determined virtual array element order and the echo signals received by each of the receiving antennas, the angles of each existing detection target are calculated.

2. The method according to claim 1, characterized in that, The step of determining the virtual array element order that minimizes the phase difference between the first virtual array element and the second virtual array element based on each of the echo signals includes: Extract the first phase of the first echo signal received by the first receiving antenna and the second phase of the second echo signal, and extract the third phase of the first echo signal received by the second receiving antenna and the fourth phase of the second echo signal; wherein, the first echo signal is the signal transmitted by one of the first transmitting antenna and the second transmitting antenna, and the second echo signal is the signal transmitted by the other; Calculate the first difference between the second phase and the third phase, and the second difference between the first phase and the fourth phase, and compare the relative magnitudes of the first difference and the second difference. Based on the relative size, the echo signals corresponding to the first virtual array element and the second virtual array element are determined, and the virtual array element sorting is obtained.

3. The method according to claim 2, characterized in that, The echo signals corresponding to the first virtual array element and the second virtual array element are determined based on the relative magnitudes. If the first difference is less than the second difference, the first echo signal received by the first receiving antenna is determined as the echo signal corresponding to the second virtual array element, and the second echo signal received by the second receiving antenna is determined as the echo signal corresponding to the first virtual array element. If the second difference is less than the first difference, the second echo signal received by the first receiving antenna is determined as the echo signal corresponding to the second virtual array element, and the first echo signal received by the second receiving antenna is determined as the echo signal corresponding to the first virtual array element.

4. The method according to claim 1, characterized in that, The step of calculating the angle of each existing detection target based on the determined virtual array element order and the echo signals received by each of the receiving antennas includes: Based on the determined virtual array element order and the echo signals received by each of the receiving antennas, the distance, ambiguity velocity and angle of each detected target in the first data frame and the second data frame are calculated. The method further includes: Based on the distance and the angle, identify the same detection target among the detection targets as the detection target to be solved; Based on the fuzzy velocity of the target to be detected in the first data frame and the second data frame, candidate values ​​of the true velocity of the target to be detected in the first data frame and candidate values ​​of the true velocity in the second data frame are determined. The candidate value that minimizes the difference in the true velocity of the target in the first data frame and the second data frame is calculated and taken as the true velocity of the target in the second data frame.

5. The method according to claim 4, characterized in that, The method further includes: The distance, fuzzy velocity, and angle of each detected target are obtained in the third data frame acquired by the binary phase-modulated radar, wherein the third data frame is after the second data frame; Based on the distance and the angle, the target to be detected is determined in the third data frame; Based on the ambiguous velocity of the target to be detected in the third data frame, determine the candidate values ​​of the true velocity of the target to be detected in the third data frame; The candidate value that minimizes the difference between the true velocity of the target in the third data frame and the true velocity in the second data frame is calculated and taken as the true velocity of the target in the third data frame.

6. The method according to claim 4, characterized in that, The candidate values ​​for the true velocity of the target to be detected are determined in the following manner: v r = m x v max + v a Wherein, v r is a candidate value of the real speed, m is a preset fuzzy number, v max is a preset maximum non-fuzzy speed, v a is the fuzzy speed of the to-be-solved detection target.

7. The method according to claim 4, characterized in that, The step of determining the same detection target among the detection targets based on the distance and the angle includes: Based on the distance and the angle, determine the first position of each first detection target in the first data frame and the second position of each second detection target in the second data frame; For any first detection target in the first data frame, calculate the difference between the first position of the first detection target and the second position of each second detection target in the second data frame; if the difference between the position of the first detection target and the second detection target is less than a preset position threshold, then the first detection target and the second detection target are determined to be the same detection target; The preset location threshold is obtained by weighted summation of the probability of the detected target belonging to each category and the distance threshold set for each category. The distance threshold set for each category is positively correlated with the size of the target in that category. The method further includes: The trajectory of each of the aforementioned detection targets is determined based on their distance, angle, and actual speed at different times.

8. A target detection device for a binary phase-modulation radar, characterized in that, An application in a radar detection system, the radar detection system comprising multiple transmitting antennas and multiple receiving antennas, the multiple transmitting antennas and the multiple receiving antennas forming a virtual array element arranged virtually, wherein a first virtual array element formed by a first transmitting antenna and a second receiving antenna overlaps with a second virtual array element formed by a second transmitting antenna and the first receiving antenna; the device includes: The antenna control module is used to control each of the transmitting antennas to transmit detection signals simultaneously and to control each of the receiving antennas to receive echo signals. The sorting determination module is used to determine the virtual array element sorting that minimizes the phase difference between the first virtual array element and the second virtual array element based on each echo signal, wherein the virtual array element sorting is used to represent the correspondence between each echo signal and each virtual array element. An angle calculation module is used to calculate the angle of each existing detection target based on the determined virtual array element order and the echo signals received by each of the receiving antennas.

9. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor, when executing a program stored in memory, implements the method described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method described in any one of claims 1-7.

Images