Method, apparatus and related device for target detection

Abstract

This application discloses a method, apparatus, and related equipment for target detection, which can be applied to an FMCW target detection system with at least two transmit and receive channels. The method includes: acquiring sampled data of echo signals; performing a range-dimensional fast Fourier transform on the sampled data; sequentially performing a velocity-dimensional fast Fourier transform, digital beamforming, and constant false alarm rate (CFAR) detection for any range gate; and obtaining the target information based on the CFAR detection results corresponding to each range gate. By performing velocity-dimensional fast Fourier transform, digital beamforming, and CFAR detection based on individual range gates, the detection performance can be ensured while achieving low-complexity CFAR detection operations, thereby improving target detection performance.

Description

[0001] This application claims priority to Chinese Patent Application No. 202111633392.1, filed on December 28, 2021, entitled “Method, Apparatus and Related Equipment for Determining Direction of Arrival”, the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to the field of target detection technology, and in particular to a method, apparatus and related equipment for target detection. Background Technology

[0003] Currently, the echo signal processing for target detection systems generally includes sequential processes such as frequency mixing, analog-to-digital conversion, sampling, range-dimensional Fourier transform, velocity-dimensional Fourier transform, and two-dimensional constant false alarm rate (CFAR) detection.

[0004] However, for target detection systems with multiple transmission and reception channels, the performance of the two-dimensional constant false alarm rate (CFAR) detection method used in the above-mentioned echo signal processing is not ideal, resulting in low target detection accuracy. Summary of the Invention

[0005] To address the aforementioned technical problems, embodiments of this application provide a method, apparatus, and related equipment for target detection. By combining factors such as merging and processing multiple transceiver channels, the performance of two-dimensional constant false alarm rate (CFAR) detection is improved, thereby enhancing the accuracy of target detection.

[0006] This application provides a target detection method applicable to an FMCW target detection system with at least two transmit / receive channels. The method includes:

[0007] Acquire the sampled data of the echo signal;

[0008] Perform a distance-dimensional Fast Fourier Transform on the sampled data;

[0009] For any distance gate, perform velocity-dimensional fast Fourier transform, digital beamforming, and constant false alarm rate (CFAR) detection sequentially; and

[0010] The target information is obtained based on the constant false alarm rate (CFAR) detection results corresponding to each distance gate;

[0011] The target information may include information such as distance, speed, and angle, and the angle may include azimuth and / or pitch angle.

[0012] In this embodiment, by performing velocity-dimensional fast Fourier transform, digital beamforming, and constant false alarm rate (CFAR) detection based on a separate distance gate, low-complexity CFAR detection operations can be achieved while ensuring detection performance, thereby improving target detection performance.

[0013] In some optional embodiments, based on the constant false alarm rate (CFAR) detection results corresponding to each distance gate, direction-of-arrival (DOA) estimation is continued to obtain the target information; including:

[0014] Based on the constant false alarm rate (CFAR) detection results corresponding to each distance gate, direction of arrival (DOA) estimation is continued to achieve the detection of target distance, velocity, and angle information while meeting the needs of different scenarios.

[0015] In some optional embodiments, the data to be fast Fourier transform is interpolated before performing the distance-dimensional fast Fourier transform and / or the velocity-dimensional fast Fourier transform to further improve the subsequent target detection performance.

[0016] In some optional embodiments, the interpolation process includes interpolation and extrapolation.

[0017] In some optional embodiments, the interpolation algorithm includes at least one of the Burg algorithm, Marple algorithm, and Tuft algorithm.

[0018] In some alternative embodiments, the FMCW target detection system is a MIMO radar or a SIMO radar.

[0019] In some optional embodiments, the step of performing a range-dimensional fast Fourier transform on the sampled data; and for any range gate, sequentially performing a velocity-dimensional fast Fourier transform, digital beamforming, and constant false alarm rate detection; includes:

[0020] After performing a distance-dimensional fast Fourier transform on the sampled data to obtain the complete data corresponding to the current distance gate, the target detection system can simultaneously perform a distance-dimensional fast Fourier transform on the sampled data to obtain the data corresponding to the next distance gate, thereby improving the efficiency of target detection and reducing the storage resources occupied by related data.

[0021] This application also provides a target detection apparatus, which can be applied to an FMCW target detection system with at least two transceiver channels. The apparatus may include:

[0022] The acquisition module is used to acquire the sampled data of the echo signal;

[0023] The distance-dimensional FFT processing module is used to perform a distance-dimensional fast Fourier transform on the sampled data; and

[0024] A pre-built digital processing module is used to sequentially perform velocity-dimensional fast Fourier transform, digital beamforming, and constant false alarm rate detection on any distance gate;

[0025] The target information processing module is used to obtain target information based on the constant false alarm rate (CFAR) detection results of each distance gate;

[0026] The target information may include distance, speed, and angle.

[0027] In some optional embodiments, the target information processing module includes a direction-of-arrival estimation module for performing direction-of-arrival estimation based on the constant false alarm rate (CFAR) detection results of each range gate to obtain the target information.

[0028] In some alternative embodiments, the apparatus further includes:

[0029] The interpolation module is used to perform interpolation processing on the data to be subjected to Fast Fourier Transform.

[0030] The preset digital processing module performs the distance-dimensional fast Fourier transform and / or the velocity-dimensional fast Fourier transform based on the data interpolated by the interpolation module.

[0031] This application also provides a computer device, which includes a processor and a memory: the memory is used to store program code and transmit the program code to the processor; the processor is used to execute the target detection method described in any of the above embodiments according to the instructions in the program code.

[0032] This application embodiment also provides an integrated circuit, including: a receiver for receiving echo signals; and a signal data processing module for performing signal processing and data processing on the echo signals to achieve target detection; wherein, when achieving target detection, the signal data processing module uses the method described in any one of the above to determine the information of each target.

[0033] In one possible implementation, the integrated circuit is a millimeter-wave radar chip.

[0034] This application embodiment also provides a wireless device, including: a carrier; an integrated circuit as described in any of the preceding claims, disposed on the carrier; an antenna, disposed on the carrier, or integrated with the integrated circuit to form an AiP (Antenna-In-Package) structure, an AoP (Antenna-On-Package) structure, or an AoC (Antenna-On-Chip) structure, etc., disposed on the carrier; wherein, the integrated circuit is connected to the antenna for transmitting and receiving radio signals.

[0035] This application also provides an apparatus, including: an apparatus body; and a wireless device as described in any of the preceding claims disposed on the apparatus body; wherein the wireless device is used for target detection and / or communication. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments recorded in this application. For those skilled in the art, other drawings can be obtained based on these drawings.

[0037] Figure 1a A schematic diagram of a two-dimensional distance-Doppler data spectrum;

[0038] Figure 1b A schematic diagram of a three-dimensional distance-Doppler-angle data spectrum;

[0039] Figure 2 This is a schematic flowchart of a target detection method in an embodiment of this application;

[0040] Figure 3a This is a schematic diagram of the three-dimensional sampling-chirp-receive channel data spectrum;

[0041] Figure 3b A schematic diagram of the three-dimensional distance-chirp-receiver channel data spectrum;

[0042] Figure 3c This is a schematic diagram of the chirped-receive channel data spectrum for distance gate k';

[0043] Figure 3d This is a schematic diagram of the Doppler-receiver channel data spectrum for range gate k';

[0044] Figure 3e A schematic diagram of the Doppler-angle data spectrum for the range gate k';

[0045] Figure 3f This is a schematic diagram of a three-dimensional distance-velocity-angle data spectrum;

[0046] Figure 3g For the corresponding Figure 3c A schematic diagram of the chirped-receive channel data spectrum after interpolation for the distance gate k';

[0047] Figure 3h For based on Figure 3g A schematic diagram of the data spectrum of the range gate-interpolated chirp-receive channel after interpolating each range gate k';

[0048] Figure 4This is a schematic diagram of the structure of a target detection device according to an embodiment of this application;

[0049] Figure 5 This is a schematic diagram of the hardware structure of a device in an embodiment of this application. Detailed Implementation

[0050] First aspect:

[0051] In practical applications, when a target detection system detects targets within its detectable area, the transmitting antenna in the system can transmit a frequency-modulated continuous wave (FMCW) signal containing several chirps. The echo signal formed after the FMCW signal is refracted and / or reflected by the target can be received by the receiving antenna in the target detection system. The target detection system can be an antenna array system with at least two transmit and receive channels, such as a multiple-input multiple-output (MIMO) radar system. MIMO radar systems can achieve high angular resolution for millimeter-wave radar and have wide applications in autonomous driving, remote sensing, navigation, and resource exploration. A typical MIMO radar system has N transmitting antennas (T... X ) and M receiving antennas (R X In this embodiment, N and M are both positive integers greater than 1. By arranging the antennas appropriately, a virtual antenna array with N×M transmit and receive channels can be formed. Of course, the target detection system can also be other systems with multiple receiving antennas, such as a single-input multi-output (SIMO) system. That is, in the antenna array, the number of transmitting antennas N and the number of receiving antennas M can both be positive integers greater than or equal to 1, and the sum of N and M can be greater than or equal to 3. This embodiment does not impose any limitations on this.

[0052] For the received echo signal, the target detection system can perform processes such as mixing, analog-to-digital conversion (ADC), sampling, Fast Fourier Transform (FFT), Constant False Alarm Rate (CFAR), and Direction of Arrival (DoA) estimation to obtain a data spectrum containing dimensions such as the target's distance, velocity, and angle relative to the detection system. The velocity dimension in the data spectrum can also be called the Doppler dimension, and the angle can include azimuth and / or elevation.

[0053] For example, when the target detection system performs range-dimensional FFT and velocity-dimensional FFT sequentially, it can obtain the following: Figure 1a The two-dimensional data spectrum shown is represented by each square on the left side of Figure 1, which represents a set of two-dimensional data. Each set of two-dimensional data includes a distance dimension and a Doppler dimension.

[0054] Optionally, when the target detection system performs angular FFT (such as azimuth FFT) or digital beamforming (DBF) based on the above two-dimensional data, it can obtain three-dimensional data including range dimension, Doppler dimension, and angular dimension (or beam space dimension), such as... Figure 1b As shown.

[0055] Optionally, each small cube on the right side of Figure 1 represents a set of three-dimensional data, including data in one range dimension, one Doppler dimension, and one angular dimension. To maximize the system's receiving gain and improve target detection performance, multi-antenna target detection systems typically perform three-dimensional constant false alarm rate (3D-CFAR) processing on this three-dimensional data. Specifically, this involves performing a three-dimensional search on the data and then performing DoA (Does-of-Aspect) angle determination based on the 3D-CFAR output to determine the range, velocity, and / or angle of each target. Since the CFAR processing also yields some angular information, DoA processing can be optional in some applications. That is, DoA processing is not required; CFAR processing alone can provide the target's angular information, thereby maximizing the radar system's receiving gain and improving target detection performance.

[0056] The second aspect:

[0057] Based on the aforementioned first aspect of the relevant embodiments, after the Doppler FFT, the Doppler FFT result can be preprocessed to obtain a two-dimensional distance-angle data spectrum, which can replace the three-dimensional distance-Doppler-angle (or beam space dimension) data spectrum obtained by using angle-dimensional FFT or DBF. Subsequently, the target information can be obtained simply through 2D-CFAR. In practical applications, compared with 3D-CFAR, the computational complexity of two-dimensional search of two-dimensional data is lower, which means that the resources occupied by industrialization, whether using software or hardware, will be less, which can further promote the industrialization of the entire system.

[0058] Third aspect:

[0059] Based on the aforementioned second aspect of the related embodiments, in order to maintain the low complexity performance of 2D-CFAR and at the same time make the detection performance of 2D-CFAR as close as possible to or even reach the detection performance of 3D-CFAR in the first aspect of the related embodiments, after performing range-dimensional FFT processing, velocity-dimensional FFT processing, DBF processing, and CFAR processing can be performed sequentially for each range gate. Since the CFAR processing is performed on a fixed range gate, the CFAR processing at this time is a two-dimensional calculation. That is, while maintaining the low complexity performance of 2D-CFAR, the system also takes into account factors such as the merging and processing of signals between the transmitting and receiving channels, so that the target detection system can maximize the radar system's receiving gain, thereby improving the system's target detection performance.

[0060] In some optional embodiments, after performing CFAR processing on each distance gate, DoA processing can also be performed based on the CFAR results of each distance gate to obtain the target's angle information.

[0061] In some optional embodiments, before performing Doppler FFT processing on any distance gate, the distance FFT result corresponding to the distance gate can be preprocessed by abstract mapping such as interpolation (interpolation and / or extrapolation), and then the above-mentioned distance FFT processing, DBF processing and CFAR processing are performed on the preprocessed result corresponding to the distance gate to further improve the accuracy of target detection.

[0062] In the first aspect of the related embodiments, since it employs 3D-CFAR, the solution in this embodiment is suitable for scenarios where the difficulty of software and hardware implementation does not need to be considered and CFAR performance is compared. In the second aspect of the related embodiments, regarding the preprocessing operation and the subsequent 2D-CFAR operation, since the characteristics of signal merging and processing between different transmit and receive channels (or antennas) are not effectively utilized, the detection performance of 2D-CFAR may be lower than that of the aforementioned 3D-CFAR. Therefore, this related solution is suitable for scenarios where the requirements for CFAR performance are not too high, but the requirements for software and hardware implementation difficulty are low. In the third related embodiment, since after the range dimension FFT processing, velocity dimension FFT processing, DBF processing and CFAR processing are performed sequentially for each range gate, and the CFAR is a two-dimensional search estimation, the software and hardware implementation requirements are relatively low. At the same time, since the relevant characteristics such as the merging and processing of signals between different transmission and reception channels (or antennas) are taken into account, the detection performance of CFAR can approach or even reach the detection performance of CFAR in the second related embodiment. Therefore, it can be widely applied to scenarios with low software and hardware implementation requirements and high requirements for CFAR detection performance.

[0063] The embodiments described above will now be described in detail with reference to the accompanying drawings:

[0064] See Figure 2 , Figure 2 A flowchart illustrating a target detection method is shown. This method can be applied to target detection systems, such as MIMO radar systems or SIMO radar systems. Specifically, the method may include:

[0065] S201: Acquire sampling data.

[0066] The target detection system can transmit an FMCW signal using at least one transmitting antenna. This FMCW signal is reflected by a target within the detectable area of ​​the system, forming an echo signal. After receiving the echo signal, the target detection system performs an analog-to-digital conversion (ADC) to obtain a digital signal, and then samples the digital signal to obtain sampled data containing baseband information.

[0067] For example, the target detection system obtains the following based on the echo signals received by multiple sets of receiving antennas: Figure 3a The sampled data shown, i.e., the three-dimensional sample-chirp-receive channel data spectrum, can be specifically represented as: x n,c,aWhere n is the index of the sample within a chirp, where n = 1 represents the data sampled at the first sampling point within the chirp, n = 2 represents the data sampled at the second sampling point within the chirp, and so on. The value of n ranges from 0 to n < N, where N is the total number of sampling points within a chirp. c is the index of the chirp within a frame of signal, where c ranges from 0 to c < C, where C is the total number of chirs contained in a frame of signal. a is the index of the receiving channel, where a ranges from 0 to a < A, where A is the total number of receiving channels, which can be determined based on the number of receiving antennas.

[0068] S202: Perform a distance-dimensional Fast Fourier Transform on the sampled data.

[0069] After obtaining sampled data based on echo signals, the target detection system can perform a Fast Fourier Transform (FFT) on the sampled data in the range dimension to obtain, as shown below. Figure 3b The three-dimensional range-chirp-receive channel data spectrum shown is the dataset X containing the range gate index k, chirp index c, and receive channel index a. k,c,a Where k takes values ​​in the range 0 ≤ k < K-1, and K is the total number of distance gates, which can be a value set in advance according to requirements, such as 512.

[0070] As examples, a target detection system may specifically employ the following formula (1) to perform a range-dimensional FFT on the sampled data:

[0071]

[0072] S203: For any distance gate, operations such as velocity-dimensional fast Fourier transform, digital beamforming, and constant false alarm rate detection can be performed sequentially.

[0073] Target detection system after obtaining Figure 3b The data spectrum shown below, as Figure 3c As shown, a velocity-dimensional FFT can be performed on any range gate k' in the Doppler dimension, that is, a separate velocity-dimensional FFT is performed on the range gate k', resulting in the following: Figure 3d The Doppler-receive channel data spectrum of the range gate k' is shown; then the range gate k' is matched. Figure 3d The Doppler-receiver channel data spectrum shown is subjected to constant false alarm rate (CFAR) detection to obtain, as... Figure 3e The Doppler-angle data spectrum of the range gate k' is shown below. Finally, by summarizing the Doppler-angle data spectra of the range gates, we can obtain the following... Figure 3fThe diagram shows a three-dimensional range-velocity-angle target information data spectrum. In this process, since Doppler FFT, DBF, and CFAR operations are performed separately for each range gate k' after the range-dimensional FFT, factors such as merging and processing between different transmit and receive channels are comprehensively considered. This maximizes the receiving gain of the detection system. Furthermore, because CFAR is performed separately for each range gate—that is, a 2D-CFAR operation—low complexity in CFAR implementation is ensured.

[0074] For example, the target detection system may employ the following formula (2) to... Figure 3c The following shows the velocity dimension FFT processing of the chirped-received channel data spectrum for the distance gate k':

[0075]

[0076] Where P is the total number of Doppler gates, which can be a pre-defined value, such as 512, etc.

[0077] As an example of implementation, the target detection system can be used to detect targets using the following formula (3). Figure 3b The Doppler-receiver channel data spectrum shown by the distance gate k' is processed using DBF:

[0078]

[0079] Among them, Z k’,c,b The target data obtained from DBF processing, where b indicates the orientation angle, B is the preset maximum orientation angle, and v a,b The steering vector coefficient of the receiving channel a at the direction angle b. Typically, Z... k’,c,b The larger the value of , the higher the probability that the target is at the direction angle b.

[0080] In another possible implementation, in order to further improve the accuracy of target detection, interpolation operations such as interpolation and / or extrapolation can be performed on the data to be processed before performing the above-mentioned digital signal processing steps such as range-dimensional FFT, velocity-dimensional FFT, DBF and / or CFAR. This preprocessing operation makes the results of subsequent digital signal processing more accurate, thereby improving the target recognition resolution and accuracy of the target detection system.

[0081] For example, targeting Figures 3a-3f The data spectra shown can all be partially or fully interpolated before subsequent operations. For example, before performing a distance-dimensional FFT, the data can be interpolated along the sampling dimension. Figure 3a The sample-chirp-receive channel data spectrum is interpolated, and then a distance-dimensional FFT operation is performed based on the interpolated data spectrum; similarly, this can also be done on the... Figure 3b The distance-chirp-receive channel shown is interpolated along the chirp dimension, and then velocity dimension FFT is performed for each distance gate.

[0082] like Figure 3c As shown, after interpolating the distance gate k' along the chirp dimension, we can obtain... Figure 3g The interpolated data spectrum is shown, and then based on Figure 3g The data spectrum shown is subjected to a velocity-dimensional FFT operation with respect to the distance gate k' to obtain the following... Figure 3d The data spectrum is shown below. The data spectrum corresponding to each distance gate can be interpolated sequentially to form the following... Figure 3h After obtaining the data spectrum shown, velocity-dimensional FFT processing is performed on each range gate separately. Alternatively, velocity-dimensional FFT processing can be performed on a range gate immediately after over-interpolation, thus avoiding the need to form a data spectrum as shown. Figure 3h The data spectrum shown can be used for specific operational steps based on actual needs.

[0083] For example, targeting Figure 3a The data spectrum x k,c,a The updated data spectrum obtained after interpolation can be represented as follows: Where d is the index of the chirp after interpolation, and the value of d is in the range of 0 ≤ d < D. D is the total number of chirps included in a frame of signal after interpolation. The value of D is greater than the value of C. For example, if the value of C is 128, then the value of D can be 256 or 512, etc.

[0084] Correspondingly, the target detection system uses the interpolated data spectrum When performing distance-dimensional FFT processing, the following formula (4) can be used:

[0085]

[0086] Alternatively, the target detection system can use the following formula (5) to analyze the data spectrum. Perform DBF processing:

[0087]

[0088] It should be noted that, Figure 3a -f is just an illustration and is used to limit the amount of data. Figure 3g-3h The black "data blocks" represent the newly added data from interpolation, such as compared to... Figure 3c , Figure 3g For the same distance gate and receiving channel, two "data" are interpolated in the chirp dimension.

[0089] It is worth noting that the target detection system, based on interpolation, performs velocity-dimensional FFT transformation and DBF processes on a distance-gate basis to obtain target data. Therefore, when further performing CFAR processing on the target data, the system can sequentially perform CFAR processing on the target data corresponding to each distance gate. Since the distance dimension value of the target data corresponding to each distance gate is fixed (i.e., the k value in the above formulas), the CFAR processing of the target data by the target detection system is a two-dimensional computation process. Compared to a three-dimensional search process, this effectively reduces the complexity of data processing, thereby reducing the resource consumption required for data processing and further improving the performance of target detection.

[0090] In an optional embodiment, after performing the DBF described above, the DoA operation can continue, specifically as follows:

[0091] S204: Based on the constant false alarm rate (CFAR) detection results corresponding to each distance gate, continue to estimate the direction of arrival (DoA).

[0092] In this embodiment, the target detection system can directly determine the target DoA based on the CFAR processing results of the target data. In other possible implementations, the target detection system may first perform CRAF processing on the target data to obtain an initial processing result, and then perform angle resolution processing on this initial processing result to obtain the final target DoA. For example, the target detection system can use a maximum likelihood (ML) search method to search for the target DoA from the initial processing result. For instance, the target detection system can determine candidate DoAs based on the initial processing result and obtain the angle value of the candidate DoA. Then, based on a preset angle threshold, the target detection system can calculate the angle interval to be confirmed, centered on the angle of the first target, and perform at least a two-dimensional ML search within this angle interval to obtain the final target DoA.

[0093] It should be noted that during the target detection system's determination of the DoA (Domain of Analysis), for each data processing step, the system can complete the processing of all data in the current operation before proceeding to the next. For example, during step S202, the target detection system can obtain all range gate data before starting step S203 to obtain the velocity dimension FFT processing results corresponding to each range gate. In other possible implementations, since the target detection system performs CFAR processing on target data sequentially, on a dataset basis, the system can directly initiate the velocity dimension FFT processing on the data corresponding to a range gate after obtaining that range gate's data. After obtaining the velocity dimension FFT result for that range gate, the system can directly perform subsequent DBF and CFAR processing on that velocity dimension FFT result. This not only improves the efficiency of target detection but also eliminates the need to save target data that has already been processed, thereby reducing the storage resources consumed during target detection.

[0094] Furthermore, embodiments of this application also provide an apparatus for target detection, which can be used to implement the target detection method in the embodiments of this application. See also... Figure 4 , Figure 4 This illustration shows a schematic diagram of a target detection device according to an embodiment of the present application. The device 300 may include:

[0095] Acquisition module 301 is used to acquire sampled data, which can be obtained by the target detection system through analog-to-digital conversion of the received echo signal, such as... Figure 3a The data spectrum of the chirped-sampled-received channel is shown.

[0096] The distance-dimensional FFT processing module 302 can be used to perform distance-dimensional FFT processing on the above-mentioned sampled data to obtain, for example... Figure 3b The distance-sampling-receiving channel data spectrum is shown.

[0097] Pre-installed digital processing module 303, for Figure 3b For any distance gate in the range, sequentially perform constant false alarm rate (CFAR) detection methods such as velocity-dimensional FFT, DBF, and CFAR. The preset digital processing module 303 can complete the data processing for all distance gates in the range-dimensional FFT processing module 302 (i.e., obtain data such as...). Figure 3b After processing the data spectrum shown, the velocity-dimensional FFT, DBF, and CFAR constant false alarm rate detection are performed sequentially for each distance gate. Alternatively, the data processing for any distance gate can be completed in the distance-dimensional FFT processing module 302 (i.e., obtaining the data spectrum shown). Figure 3bAfter processing the data spectrum corresponding to any distance gate, the velocity dimension FFT, DBF and CFAR constant false alarm rate detection are immediately performed on the distance gate in sequence. At this time, the distance dimension FFT processing module 302 and the preset digital processing module 303 can work simultaneously to effectively reduce the storage resources occupied by the relevant data in the digital signal processing process.

[0098] The target information processing module 304 can be used to obtain target information based on the constant false alarm rate (CFAR) detection results of each distance gate (i.e., ...). Figure 3f The data spectrum shown; wherein the target information includes distance, velocity and / or angle (azimuth and / or pitch angle), etc.

[0099] In this embodiment, the velocity-dimensional FFT, DBF, and CFAR constant false alarm rate (CFAR) detection operations performed separately based on the distance gate ensure that CFAR CFAR detection is a two-dimensional operation, thereby ensuring low data processing complexity and fully considering the interrelationship between the transmitting and receiving channels, thus maximizing the receiving gain of the target detection system.

[0100] In one possible implementation, the device 300 described above may further include a difference module, which can be used to perform a difference module on the data to be fast Fourier Transformed (e.g., before the distance dimension FFT processing module 302 performs the distance dimension fast Fourier Transform and / or the preset digital processing module 303 performs the velocity dimension fast Fourier Transform). Figures 3a-3c The data spectrum shown can be subjected to interpolation processing, such as interpolation or extrapolation, to further improve the performance of subsequent target detection. At least one of the Burg algorithm, Marple algorithm, and Tuft algorithm can be used for the above interpolation processing.

[0101] In one possible implementation, the target information processing module 304 may further include a direction-of-arrival estimation unit for performing direction-of-arrival estimation based on the results of constant false alarm detection of each range gate to obtain the target information.

[0102] It is worth noting that the target detection device 300 described in this embodiment can correspond to the above-mentioned Figure 2 The target detection method described in the illustrated embodiment, and the specific implementation details of each module and unit in this embodiment, can be found in the foregoing. Figure 2 The relevant parts of the method embodiments shown are described in detail and will not be repeated here.

[0103] Additionally, this application also provides a device. (See attached document.) Figure 5 , Figure 5A schematic diagram of the hardware structure of a device according to an embodiment of this application is shown. The device 400 includes a processor 401 and a memory 402. The memory 402 is used to store program code and transmit the program code to the processor 401. The processor 401 is used to execute the following steps according to the instructions in the program code:

[0104] Acquire sampling data, which is obtained by sampling the echo signal after analog-to-digital conversion; perform range-dimensional fast Fourier transform on the sampling data; for any range gate, sequentially perform velocity-dimensional fast Fourier transform, digital beamforming, and constant false alarm rate (CFAR) detection; and obtain target information based on the CFAR detection results corresponding to each range gate.

[0105] Furthermore, the processor 401 can also be used to execute the specific steps or other steps described in the above method embodiments according to the instructions in the program code.

[0106] In some optional embodiments, this application also provides an integrated circuit, which may include a receiver and a signal data processing module; wherein, the receiver can be used to receive echo signals, and the signal data processing module can be used to perform analog-to-digital conversion on the echo signals and digital signal processing on the signals obtained by analog-to-digital conversion to achieve target detection. When achieving target detection, the signal data processing may employ the target detection methods described in the above embodiments to determine relevant information such as distance, speed and angle of each target.

[0107] Optionally, the integrated circuit can be a chip structure, such as a millimeter-wave radar chip. Of course, it can also be implemented in other hardware.

[0108] In one embodiment, this application also provides a wireless device, including: a carrier; an integrated circuit as described in the above embodiment, disposed on the carrier; and an antenna, disposed on the carrier; wherein the integrated circuit is connected to the antenna via a first transmission line for transmitting and receiving radio signals. The carrier can be a printed circuit board (PCB), and the first transmission line can be a PCB trace. Furthermore, the aforementioned integrated circuit can also be integrated with the antenna into a single device to form a structure such as AiP, AoP, or AoC.

[0109] In one embodiment, this application also provides a device, including: a device body; and a wireless device as described above disposed on the device body; wherein the wireless device is used for target detection and / or communication.

[0110] Specifically, based on the above embodiments, in one embodiment of this application, the wireless device may be disposed outside the device body; in another embodiment, the wireless device may be disposed inside the device body; and in other embodiments, the wireless device may be partially disposed inside the device body and partially disposed outside the device body. This application does not limit the scope of the embodiments and the specific method depends on the circumstances.

[0111] It should be noted that wireless devices can achieve functions such as target detection and communication by transmitting and receiving signals.

[0112] In an optional embodiment, the aforementioned device body can be a component or product applied in fields such as smart homes, transportation, smart home systems, consumer electronics, surveillance, industrial automation, in-cabin testing, and healthcare. For example, the device body can be intelligent transportation equipment (such as automobiles, bicycles, motorcycles, ships, subways, trains, etc.), security equipment (such as cameras), smart wearable devices (such as wristbands, glasses, etc.), smart home devices (such as televisions, air conditioners, smart lights, etc.), various communication devices (such as mobile phones, tablets, etc.), as well as devices such as barriers, intelligent traffic lights, intelligent signs, traffic cameras, and various industrial robotic arms (or robots). It can also be various instruments for detecting vital signs and various devices equipped with such instruments. The wireless device can be any of the wireless devices described in any embodiment of this application. The structure and working principle of the wireless device have been described in detail in the above embodiments and will not be repeated here.

[0113] This application also provides a computer-readable storage medium. The methods described in the above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any combination thereof. If implemented in software, the functionality can be stored as one or more instructions or code on or transmitted on a computer-readable medium. A computer-readable medium can include computer storage media and communication media, and can also include any medium that can transfer a computer program from one place to another. The storage medium can be any target medium accessible by a computer.

[0114] As an optional design, a computer-readable medium may include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium targeted to carry or to store the required program code in the form of instructions or data structures, and accessible by a computer. Furthermore, any connection is appropriately referred to as a computer-readable medium. For example, if software is transmitted from a website, server, or other remote source using coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave, then coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. As used herein, disks and optical discs include optical discs (CDs), laser discs, optical discs, digital optical discs, etc. Under this understanding, the technical solutions of this application can be embodied in the form of a software product, which can be stored in a storage medium such as read-only memory (ROM) / RAM, magnetic disk, optical disc, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network communication device such as a router) to execute the methods described in various embodiments or certain portions of the embodiments of this application.

[0115] The various embodiments in this specification are described in a progressive 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 device embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. The device embodiments described above are merely illustrative. Modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0116] The above description is merely an exemplary implementation of this application and is not intended to limit the scope of protection of this application.

Claims

1. A method of object detection, characterized in that, The method, applied to an FMCW target detection system with at least two transmit and receive channels, includes: Acquire the sampled data of the echo signal; Perform a distance-dimensional Fast Fourier Transform on the sampled data; For any distance gate, perform velocity-dimensional fast Fourier transform, digital beamforming, and constant false alarm rate (CFAR) detection sequentially; and Target information is obtained based on the constant false alarm rate (CFAR) detection results corresponding to each distance gate; Specifically, for any range gate, performing velocity-dimensional fast Fourier transform, digital beamforming, and constant false alarm rate detection sequentially includes: for the range gate, performing velocity-dimensional fast Fourier transform on each transmit and receive channel, and then performing digital beamforming based on the range-Doppler data of each channel of the range gate.

2. The method of claim 1, wherein, The acquisition of target information based on the constant false alarm rate (CFAR) detection results corresponding to each distance gate includes: Based on the constant false alarm rate (CFAR) detection results corresponding to each distance gate, the direction of arrival (DOA) is estimated to obtain the target information.

3. The method according to claim 1 or 2, characterized in that, Before performing a distance-dimensional Fast Fourier Transform and / or a velocity-dimensional Fast Fourier Transform, the data to be Fast Fourier Transformed is interpolated.

4. The method of claim 3, wherein, The interpolation process includes interpolation and extrapolation.

5. The method according to claim 4, characterized in that, The interpolation algorithm includes at least one of the Burg algorithm, Marple algorithm, and Tuft algorithm.

6. The method according to any one of claims 1 to 5, characterized in that, The FMCW target detection system is a MIMO radar or a SIMO radar.

7. The method according to any one of claims 1-6, characterized in that, The process of performing a range-dimensional Fast Fourier Transform on the sampled data, and sequentially performing a velocity-dimensional Fast Fourier Transform, digital beamforming, and constant false alarm rate (CFAR) detection for any range gate, includes: After performing a range-dimensional fast Fourier transform on the sampled data to obtain the complete data corresponding to the current range gate, the target detection system can perform a range-dimensional fast Fourier transform on the sampled data to obtain the data corresponding to the next range gate while sequentially performing a velocity-dimensional fast Fourier transform, digital beamforming, and constant false alarm rate detection on the data corresponding to the current range gate.

8. A target detection device, characterized in that, The device, applied in an FMCW target detection system with at least two transmit and receive channels, comprises: The acquisition module is used to acquire the sampled data of the echo signal; The distance-dimensional FFT processing module is used to perform a distance-dimensional fast Fourier transform on the sampled data; and A pre-built digital processing module is used to sequentially perform velocity-dimensional fast Fourier transform, digital beamforming, and constant false alarm rate detection on any distance gate; The target information processing module is used to obtain target information based on the constant false alarm rate (CFAR) detection results of each distance gate; The target information includes distance, speed, and angle; While the preset digital processing module sequentially performs velocity-dimensional fast Fourier transform, digital beamforming, and constant false alarm rate detection on the data corresponding to the current distance gate, the distance-dimensional FFT processing module performs distance-dimensional fast Fourier transform on the sampled data to obtain the data corresponding to the next distance gate.

9. The apparatus according to claim 8, characterized in that, The target information processing module includes a direction-of-arrival estimation module, which is used to estimate the direction of arrival based on the constant false alarm rate (CFAR) detection results of each distance gate to obtain the target information.

10. The apparatus according to claim 8 or 9, characterized in that, The device further includes: The interpolation module is used to perform interpolation processing on the data to be subjected to Fast Fourier Transform. The preset digital processing module performs the distance-dimensional fast Fourier transform and / or the velocity-dimensional fast Fourier transform based on the data interpolated by the interpolation module.

11. A computer device, characterized in that, The computer device includes a processor and memory: The memory is used to store program code and transmit the program code to the processor; The processor is configured to execute the target detection method according to any one of claims 1 to 7 according to the instructions in the program code.

12. An integrated circuit, characterized in that, include: The receiving end is used to receive echo signals; as well as The signal data processing module is used to perform signal processing and data processing on the echo signal to achieve target detection; When performing the target detection, the signal data processing module uses the method described in any one of claims 1-7 to determine the information of each target.

13. The integrated circuit according to claim 12, characterized in that, The integrated circuit is a millimeter-wave radar chip.

14. A wireless device, characterized in that, include: Carrier; The integrated circuit as described in any one of claims 12 or 13 is disposed on the carrier. The antenna is disposed on the carrier, or integrated with the integrated circuit to form an AiP, AoP, or AoC structure and disposed on the carrier. The integrated circuit is connected to the antenna and is used to transmit and receive radio signals.

15. A device, characterized in that, include: Equipment body; as well as The wireless device as described in claim 14 is disposed on the device body; The radio device is used for target detection and / or communication.

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