Target detection method and device, computer equipment and storage medium

Abstract

The invention relates to a target detection method and device, computer equipment and a storage medium. The method comprises the following steps: generating a distance Doppler spectrum according to echo data corresponding to partial unequally spaced signals transmitted based on preset waveform parameters; based on a preset rearrangement index table, rearranging the distance Doppler spectrum to enable mutual interference spurious signals in the distance Doppler spectrum to be gathered in a preset area, and obtaining rearrangement data; the preset rearrangement index table is determined based on the preset waveform parameter and the antenna array arrangement of the millimeter wave radar; and performing target detection based on the rearranged data to obtain a target detection result. By adopting the method, the target detection accuracy and the resource utilization rate can be improved.

Description

Technical Field

[0001] This application relates to the field of radar technology, and in particular to a target detection method, apparatus, computer equipment, and storage medium. Background Technology

[0002] Today, millimeter-wave radar is widely used in the field of target detection, while vehicle-mounted radar systems have high requirements for detection accuracy and weak target detection capabilities.

[0003] Traditional technologies employ target detection methods using non-uniformly spaced waveform processing links, combined with DA (Doppler-Azimuth) processing links, which aids in weak target detection. However, in DDMA systems, MIMO channel rearrangement under non-uniformly spaced code patterns inevitably generates spurious crosstalk signals distributed along the angular dimension. These spurious signals create numerous false detection points after detection, affecting not only the screening of normal targets but also wasting storage, processor, and time resources.

[0004] This shows that traditional technologies still suffer from low target detection accuracy and low resource utilization. Summary of the Invention

[0005] Therefore, it is necessary to provide a target detection method, apparatus, computer equipment, and storage medium that can improve the accuracy of target detection and the utilization rate of resources, in order to address the above-mentioned technical problems.

[0006] Firstly, this application provides a target detection method applied to millimeter-wave radar, the target detection method comprising:

[0007] A range Doppler spectrum is generated based on the echo data corresponding to a portion of non-equally spaced signals transmitted according to preset waveform parameters.

[0008] Based on a preset rearrangement index table, the range-Doppler spectrum is rearranged so that the interfering spurious signals in the range-Doppler spectrum are concentrated in a preset region to obtain rearranged data; the preset rearrangement index table is determined based on the preset waveform parameters and the antenna array arrangement of the millimeter-wave radar.

[0009] Target detection is performed based on the rearranged data to obtain the target detection results.

[0010] In one embodiment, the preset waveform parameters include the minimum phase step code interval and the phase step code coefficients for each transmission channel, and the target detection method further includes:

[0011] Based on the minimum and maximum phase step codes, the maximum value of the phase step code coefficients is determined.

[0012] Based on the maximum value of the phase step code coefficient and the phase step code coefficient, the phase step value of each transmission channel is determined;

[0013] Each of the transmission channels is controlled to transmit partially non-equally spaced signals according to the phase step value; the difference between the phase step values ​​of any two transmission channels is an integer multiple of a fixed value.

[0014] In one embodiment, determining the preset rearrangement index table based on the preset waveform parameters and the antenna array arrangement of the millimeter-wave radar includes:

[0015] Based on the preset waveform parameters, channel demodulation mapping is performed on the initial data index to obtain a channel demodulation index sequence; the channel demodulation index sequence includes the Doppler offset position of the same target under different transmission channels due to phase stepping;

[0016] Based on the preset waveform parameters and the regular distribution of mutual interference spurious signals corresponding to the channel demodulation mapping, a spurious rearrangement index sequence is generated;

[0017] A preliminary rearranged index sequence is obtained by fusing the channel demodulation index sequence and the spurious rearrangement index sequence.

[0018] Based on the antenna array arrangement of the millimeter-wave radar, the initial rearranged index sequence is rearranged in the azimuth dimension to obtain the preset rearranged index table.

[0019] In one embodiment, the step of performing channel demodulation mapping on the initial data index based on the preset waveform parameters to obtain the channel demodulation index sequence includes:

[0020] The phase step value for each transmission channel is determined based on the preset waveform parameters;

[0021] Based on the phase step value, the Doppler index offset of the transmission channel is determined;

[0022] Based on the Doppler index offsets of the multiple transmission channels, a Doppler index sequence is obtained;

[0023] The channel demodulation index sequence is determined based on the Doppler index sequence and the number of receiving channels of the millimeter-wave radar.

[0024] In one embodiment, generating a spurious rearrangement index sequence based on the regular distribution of mutual interference spurious signals corresponding to the preset waveform parameters and the channel demodulation mapping includes:

[0025] Based on the number of receiving channels of the millimeter-wave radar, a preset area is determined; the preset area includes a continuous index interval on the Doppler plane.

[0026] Based on the minimum Doppler offset unit corresponding to the Doppler index offset of multiple transmission channels, the interfering spurious signals are indexed into the preset region to obtain a spurious rearrangement index sequence; wherein the difference between the Doppler index offsets of any two transmission channels is an integer multiple of the minimum Doppler offset unit.

[0027] In one embodiment, the azimuth-dimensional rearrangement of the preliminary rearranged index sequence based on the antenna array arrangement of the millimeter-wave radar to obtain the preset rearranged index table includes:

[0028] Based on the virtual channel physical order corresponding to the antenna array arrangement, the azimuth dimension rearrangement mapping is performed on the preliminary rearrangement index sequence to obtain a preset rearrangement index table.

[0029] In one embodiment, the target detection based on the rearranged data to obtain the target detection result includes:

[0030] Perform an azimuth angle Fourier transform on the rearranged data to obtain the Doppler azimuth spectrum;

[0031] The target detection result is obtained by performing constant false alarm rate based on the Doppler azimuth spectrum.

[0032] Secondly, this application provides a target detection device for use in millimeter-wave radar, the target detection device comprising:

[0033] The generation module is used to generate a range Doppler spectrum based on the echo data corresponding to a portion of non-equally spaced signals transmitted based on preset waveform parameters.

[0034] The rearrangement module is used to rearrange the range-Doppler spectrum based on a preset rearrangement index table, so that the interfering spurious signals in the range-Doppler spectrum are concentrated in a preset region to obtain rearranged data; the preset rearrangement index table is determined based on the preset waveform parameters and the antenna array arrangement of the millimeter-wave radar;

[0035] The detection module is used to perform target detection based on the rearranged data and obtain the target detection result.

[0036] Thirdly, this application provides a computer device including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method described above.

[0037] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described above.

[0038] The aforementioned target detection method, apparatus, computer equipment, and storage medium generate a range-Doppler spectrum based on the echo data corresponding to partially non-equally spaced signals emitted based on preset waveform parameters. Based on a preset rearrangement index table, the range-Doppler spectrum is rearranged so that interfering spurious signals in the range-Doppler spectrum are concentrated in a preset region, resulting in rearranged data. Target detection is then performed based on this rearranged data to obtain target detection results. By establishing an initial detection representation containing both target and spurious information, the interfering spurious signals can exhibit a spatially regular distribution. This allows the interfering spurious signals, originally diffusely distributed in the angular dimension, to be systematically migrated and concentrated in a preset region, forming structurally controllable rearranged data. Target detection is then performed on this basis. Because the interfering spurious signals are concentrated, the probability of false detection points can be significantly reduced. Furthermore, since complex filtering or additional storage management of spurious signals across the entire domain is unnecessary, the technical effect of improving target detection accuracy and resource utilization can be effectively achieved. Attached Figure Description

[0039] Figure 1 This is a diagram illustrating the application environment of a target detection method in one embodiment;

[0040] Figure 2 This is a flowchart illustrating a target detection method in one embodiment;

[0041] Figure 3 This is a flowchart illustrating the target detection method in another embodiment;

[0042] Figure 4 This is a waveform diagram of some non-equally spaced signals in one embodiment;

[0043] Figure 5 This is a schematic diagram showing the functional module distribution of a radar system in one embodiment;

[0044] Figure 6 This is a schematic diagram of the antenna array of a radar system in one embodiment;

[0045] Figure 7 This is a schematic diagram of the MIMO virtual array arrangement in one embodiment;

[0046] Figure 8 This is a schematic diagram comparing the stray distribution before and after stray rearrangement in one embodiment;

[0047] Figure 9 This is a structural block diagram of a target detection device in one embodiment;

[0048] Figure 10 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0050] The target detection method provided in this application embodiment can be applied to, for example... Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that terminal 102 needs to process. The data storage system can be integrated onto server 104 or placed on a cloud or other network server. Terminal 102 can also communicate with millimeter-wave radar 106 via a wired network to acquire echo data received by millimeter-wave radar 106. The echo data corresponds to echo data of partially non-equally spaced signals transmitted based on preset waveform parameters. Terminal 102 generates a range Doppler spectrum based on this echo data; it rearranges the range Doppler spectrum based on a preset rearrangement index table to concentrate the interfering spurious signals in the range Doppler spectrum into a preset region, obtaining rearranged data; the preset rearrangement index table is determined based on the preset waveform parameters and the antenna array arrangement of the millimeter-wave radar; target detection is performed based on the rearranged data to obtain target detection results. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, and IoT devices. For example, IoT devices can be smart vehicle devices, etc. Server 104 can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0051] In one embodiment, such as Figure 2 As shown, a target detection method is provided and applied to millimeter-wave radar. This method is then applied to… Figure 1 Taking terminal 102 as an example, the explanation includes the following steps:

[0052] Step S202: Generate a range Doppler spectrum based on the echo data corresponding to the partially non-equally spaced signals transmitted based on preset waveform parameters.

[0053] The preset waveform parameters can be waveform configuration information used to define the transmitted signal of the millimeter-wave radar. For example, they can include signal characteristic parameters such as modulation method, bandwidth, and periodic structure. In this embodiment, the preset waveform parameters can be used to determine the time-frequency structure of the transmitted signal, thereby affecting the characteristics of the echo data and the performance of subsequent processing links. For example, the preset waveform parameters can include linear frequency modulation parameters, non-equidistant coding parameters, and phase modulation parameters.

[0054] Partially non-uniformly spaced signals, as a type of non-uniformly spaced signal, are signals that are not completely random, but possess a specific algebraic or combinatorial structure, as opposed to completely non-uniformly spaced signals with completely random or completely coprime characteristics. It is understood that when there are finite types or periodic structures between elements in an interval sequence or between the differences of elements, they can be considered non-random and possess a certain algebraic or combinatorial structure. For example, partially non-uniformly spaced signals can be constructed by controlling the differences of elements in the interval sequence to follow an integer multiple relationship, by making the differences closed within a finite period, by making the stray Doppler values ​​symmetrical or periodically repeating, or by using segmented equally spaced or pseudo-random intervals with regular differences. This embodiment does not limit the scope of the construction of partially non-uniformly spaced signals.

[0055] Echo data can be the raw data matrix formed by digitally sampling the electromagnetic signals reflected from the target and collected by the radar receiving antenna. In this embodiment, the echo data can be obtained by mixing, amplifying, and converting the reflected signal through the receiving channel. It is understood that the echo data may contain one or more information such as the target's distance, velocity, and angle.

[0056] The range-Doppler spectrum is a two-dimensional spectrum obtained by performing Fourier transforms on the echo data in the range dimension and the Doppler dimension, respectively, to reflect the energy distribution of the target in terms of range and relative velocity, and can provide a preliminary energy distribution map that can be used for target detection.

[0057] Based on the echo data corresponding to the partially non-equally spaced signals transmitted based on preset waveform parameters, a range-Doppler spectrum is generated. This can be achieved by generating partially non-equally spaced transmitted signals using preset waveform parameters, receiving the corresponding echo data, and then sequentially performing range-dimensional FFT and Doppler-dimensional FFT processing to form a two-dimensional spectrum, thereby establishing an initial detection representation containing target and clutter information.

[0058] Step S204: Based on the preset rearrangement index table, the range Doppler spectrum is rearranged so that the interfering spurious signals in the range Doppler spectrum are gathered in the preset region to obtain rearranged data.

[0059] The preset rearrangement index table can be a set of pre-calculated and fixed index mapping rules used to indicate the new positional arrangement order of each data unit in the range-Doppler spectrum. The preset rearrangement index table is determined based on preset waveform parameters and the antenna array arrangement of the millimeter-wave radar. In this embodiment, the preset rearrangement index table can be used to guide the data units in the range-Doppler spectrum to rearrange according to specific rules, so that interfering spurious signals are concentrated in a preset area. For example, the preset rearrangement index table can be pre-calculated after the preset waveform parameters are set, or it can be calculated and fixed before executing step S200.

[0060] The antenna array arrangement of a millimeter-wave radar can be described as the geometric distribution of transmitting and receiving antennas in space within the radar system, including the number of array elements, spacing, and topology. Furthermore, the antenna array arrangement of a millimeter-wave radar can be determined during the hardware design phase, participating as an inherent system attribute in signal processing model construction. It determines the synthesis method of the MIMO virtual array and the spatial response characteristics between channels, influencing the spatial distribution of mutual interference spurious signals. In a specific embodiment, the antenna array arrangement of a millimeter-wave radar can adopt arrangements such as linear arrays, L-shaped arrays, or circular arrays.

[0061] Crosstalk spurious signals can be energy responses of non-real targets caused by the mismatch between non-equal interval code patterns and antenna mapping relationships. For example, they can be caused by asymmetry in the transmitted signal structure and crosstalk between receiving channels, and appear as discontinuously distributed energy points in the range Doppler spectrum.

[0062] Rearranged data can be a new data structure obtained by remapping the data positions of the range-Doppler spectrum according to a preset rearrangement index table. By rearranging the data, the distribution pattern of the effective target signal can be preserved while concentrating interfering spurious signals in a fixed area. In an exemplary embodiment, data units in the range-Doppler spectrum can be rewritten to new addresses according to the position mapping relationship defined in the preset rearrangement index table to achieve overall data reconstruction.

[0063] The predetermined rearrangement index table is determined based on predetermined waveform parameters and the antenna array arrangement of the millimeter-wave radar. This can be achieved by combining the system's transmitted signal structure with the antenna's physical layout, modeling and analyzing the spurious generation mechanism, deriving the regularity of the positions of interleaved spurious signals, and thus constructing rearrangement rules to aggregate spurious signals. For example, the rearrangement index table can be constructed by simulation modeling to invert the optimal index combination, or by directly calculating the rearrangement mapping relationship based on analytical formulas. This ensures that the rearrangement strategy matches the hardware and signal characteristics, guaranteeing the effectiveness and consistency of spurious signal aggregation.

[0064] Step S206: Perform target detection based on the rearranged data to obtain the target detection result.

[0065] The target detection result can be a set of real target information identified from the rearranged data, which may include one or more parameters such as target distance, velocity, and angle. The process of obtaining the target detection result may include single or multiple detections, and stable target detection results can be obtained through correction methods such as time-sliding window filtering and cross-validation of target parameters.

[0066] In this embodiment, target detection based on rearranged data can be achieved by excluding preset stray regions in the rearranged data and then performing peak detection and parameter estimation processes on the remaining regions. This can reduce the number of false detection points and improve the effectiveness and reliability of the detection output.

[0067] Taking autonomous driving perception on urban roads as an example, this embodiment can be implemented when the vehicle-mounted millimeter-wave radar detects vehicles and pedestrians ahead in a complex traffic environment. It uses some non-equidistant signals to improve resolution. After the echo data generates a range Doppler spectrum, it is rearranged using a preset rearrangement index table to concentrate the mutual interference spurious signals between MIMO channels caused by asymmetric coding in the edge region of the spectrum. Then, target detection is performed in the central effective area, thereby avoiding false alarms caused by mutual interference spurious signals. It can still accurately identify small obstacles in adjacent lanes in high-density target scenarios, reducing the resource consumption caused by the processor frequently processing invalid data.

[0068] This embodiment provides a target detection method that generates a range-Doppler spectrum based on the echo data corresponding to partially non-equally spaced signals emitted based on preset waveform parameters. The range-Doppler spectrum is then rearranged based on a preset rearrangement index table to concentrate interfering spurious signals within a preset region, resulting in rearranged data. Target detection is then performed based on this rearranged data to obtain the target detection result. By establishing an initial detection representation containing both target and spurious information, the interfering spurious signals can exhibit a spatially regular distribution. This allows the originally diffusely distributed interfering spurious signals to be systematically migrated and concentrated into a preset region, forming structurally controllable rearranged data. Target detection is then performed on this basis. Because the interfering spurious signals are concentrated, the target detection based on the rearranged data can significantly reduce the probability of false detection points. Furthermore, since there is no need for complex filtering or additional storage management of spurious signals across the entire domain, it effectively improves the accuracy of target detection and resource utilization.

[0069] In one embodiment, the preset waveform parameters include the minimum interval of the phase step code and the phase step code coefficients for each transmission channel, and the target detection method further includes:

[0070] The maximum value of the phase step code coefficients is determined based on the minimum and maximum phase step code intervals.

[0071] The phase step value for each transmission channel is determined based on the maximum value of the phase step code coefficient and the phase step code coefficient.

[0072] Each transmission channel is controlled to transmit partially non-equally spaced signals according to a phase step value; the difference between the phase step values ​​of any two transmission channels is an integer multiple of a fixed value.

[0073] The minimum interval of the phase step code can be the minimum time interval between adjacent valid symbols on the time axis in the phase-coded sequence, which can be used to constrain the basic timing resolution of non-equally spaced signals. In this embodiment, the minimum interval of the phase step code can be determined by the system clock accuracy and modulation bandwidth, serving as a positive integer factor of the phase step code coefficients.

[0074] The maximum value of the phase step code can be the maximum allowed time offset in the phase-coded sequence, representing the total duration range within a complete coding period. In an exemplary embodiment, the maximum value of the phase step code can be determined based on the frame period and the pulse repetition interval, and can be the product of the maximum value of the phase step code coefficients and the minimum interval.

[0075] The maximum value of the phase step code coefficients can be the upper limit of the normalized coefficients used to generate the actual phase step value, calculated from the minimum phase step code interval and the maximum value of the phase step code. Furthermore, the maximum value of the phase step code can be the product of the maximum value of the phase step code coefficients and the minimum interval, which can be obtained by dividing the maximum value of the phase step code by the minimum interval.

[0076] In one specific embodiment, the maximum value of the phase step code coefficient can be determined by methods such as rounding down after floating-point operations or matching preset maximum value combinations using a lookup table. This establishes an upper limit for the value of the coding coefficient, limits the complexity of the signal structure, and avoids increased mutual interference due to excessive code density.

[0077] The phase step code coefficients can be the coefficient values ​​used by each transmit channel to generate its specific phase step value. They can determine the time offset mode of the signal in that channel and calculate the phase increment of the phase shifter. In this embodiment, the phase step code coefficients can be independently configured for each channel within a preset range, and the actual phase step value is generated according to the minimum interval. Furthermore, the phase step code coefficients and the maximum value of the phase step code satisfy a proportional relationship. It can be understood that the phase step code coefficients can achieve differentiated control of the signal timing of different transmit channels, thereby supporting the construction of MIMO virtual arrays and affecting the Doppler index offset.

[0078] The phase step value for each transmit channel can be the actual time offset calculated based on the phase step code coefficients and the minimum interval. This corresponds to the adjustment of the transmission timing of the signal in that channel within the frame and is used to control the phase increment of the phase shifter. For example, the phase step value for each transmit channel can be calculated channel-by-channel by multiplying the phase step code coefficients by the minimum phase step code interval. By determining the phase step value for each transmit channel separately, the transmission timing of partially non-equally spaced signals in each transmit channel can be precisely controlled, forming a controlled partially non-equally spaced transmission sequence, ensuring that the difference between the phase step values ​​of any two channels is an integer multiple of a fixed value.

[0079] Controlling each transmission channel to transmit a portion of the non-equally spaced signals according to a phase step value can be achieved by converting the calculated phase step value into a time delay command and loading it into the trigger timing controller of the corresponding transmission channel to control the transmission of the non-equally spaced signals. The difference between the phase step values ​​of any two transmission channels is an integer multiple of a fixed value, thereby enhancing the quasi-orthogonality between multi-channel signals, suppressing the diffusion of intermodulation products caused by phase mismatch, and reducing the randomness of interfering spurious signals.

[0080] This embodiment provides a target detection method that determines the maximum value of the phase step code coefficients based on the minimum and maximum phase step code intervals. It then determines the phase step value for each transmission channel based on the maximum and phase step code coefficients. Each transmission channel is controlled to transmit a portion of non-equally spaced signals according to the phase step value, ensuring that the difference between the phase step values ​​of any two transmission channels is an integer multiple of a fixed value. By limiting the coding range and deriving the maximum coefficient value, coefficients are assigned to each channel, and the phase step value is calculated, constraining the relationship between the phase step value differences. This reduces the randomness and dispersion of interfering spurious signals, forms a structured temporal distribution, improves the predictability of the signal system, and helps the generated echo data exhibit more concentrated interference characteristics. Ultimately, this achieves the technical effect of improving target detection accuracy and resource utilization.

[0081] In one embodiment, determining the preset rearrangement index table based on preset waveform parameters and the antenna array arrangement of the millimeter-wave radar includes:

[0082] Based on preset waveform parameters, channel demodulation mapping is performed on the initial data index to obtain the channel demodulation index sequence; the channel demodulation index sequence includes the Doppler offset position of the same target under different transmission channels due to phase stepping;

[0083] Based on the regular distribution of mutual interference spurious signals corresponding to preset waveform parameters and channel demodulation mapping, a spurious rearrangement index sequence is generated;

[0084] A preliminary rearranged index sequence is obtained by fusing the channel demodulation index sequence and the spurious rearranged index sequence.

[0085] Based on the antenna array arrangement of millimeter-wave radar, the initial rearranged index sequence is rearranged in the azimuth dimension to obtain a preset rearranged index table.

[0086] The initial data index can be a set of logical position identifiers representing the original data units in the range-Doppler spectrum, used to map the signal distribution in the range-Doppler two-dimensional space. For example, the initial data index can be obtained through range-to-Doppler fast Fourier transform processing.

[0087] Channel demodulation mapping can decouple multi-channel received data based on the phase coding characteristics of the transmitted signal, thereby restoring the independent contribution of each transmitted channel and realizing the separation of the mixed response of multiple transmitted channels in a multiple-input multiple-output system. For example, channel demodulation mapping can calculate the frequency shift relationship caused by signal superposition between different channels based on the coding timing and phase step rules contained in preset waveform parameters. For instance, demodulation mapping can be achieved through methods such as phase inversion, frequency offset compensation, and quadrature decoding.

[0088] A channel demodulation index sequence can be an ordered set of indices recording the positions of each effective signal component in the range-Doppler spectrum after channel demodulation mapping. This allows it to preserve the correct positional information of the real target after multi-channel synthesis. By applying the channel demodulation index sequence, the Doppler offset position corresponding to the real target can be re-generated.

[0089] Doppler offset can be caused by differences in phase step values ​​introduced by different transmission channels, resulting in the same target appearing with a non-zero frequency offset in the Doppler dimension. Accordingly, the Doppler offset position can be the offset position of the same target, thus reflecting the true position characteristics of the target after demodulation by multiple input multiple output channels.

[0090] Based on preset waveform parameters, channel demodulation mapping is performed on the initial data index to obtain a channel demodulation index sequence. This can be achieved by using the encoding timing and phase step rules defined in the preset waveform parameters to analyze the influence of each transmission channel on the echo signal and adjust the position of the initial data index accordingly, forming a channel demodulation index sequence that reflects the Doppler shift of the actual target. Furthermore, the mapping relationship can be determined by looking up a preset phase encoding table, or the index offset can be dynamically calculated using a demodulation algorithm. This allows for the decoupling of multi-channel signals in a multi-input multi-output system, accurately restoring the theoretical position of the effective target in the range-Doppler spectrum.

[0091] The regular distribution of cross-interference spurious signals can be achieved under conditions of non-equal interval coding patterns and multi-input multi-output channel rearrangement. The cross-interference spurious signals exhibit a predictable spatial distribution pattern in the range-Doppler spectrum, and this regular distribution allows the spurious signals to be actively guided to a specific region. For example, the regular distribution of cross-interference spurious signals can originate from signal structure asymmetry and non-ideal orthogonality between channels. For instance, depending on the preset waveform parameters and the characteristics of the channel demodulation mapping, different distribution patterns may emerge, such as periodic strip distributions, mirror-symmetric distributions, or discrete cluster distributions.

[0092] Spurious rearrangement index sequences are sets of index mapping rules used to guide interfering spurious signals to a concentrated region. This allows for the energy aggregation of false signals, preventing their widespread diffusion within the detection domain. For example, by analyzing the unwanted response paths generated during channel demodulation, an index arrangement that converges these paths can be designed in reverse, thus obtaining the spurious rearrangement index sequence.

[0093] Correspondingly, based on the regular distribution of mutual interference spurious signals corresponding to preset waveform parameters and channel demodulation mapping, a spurious rearrangement index sequence is generated. This can be used to analyze the fixed patterns of mutual interference spurious signals under specific waveform parameters and demodulation mapping, and to concentrate them into a specified preset area through reverse mapping rules.

[0094] Fusion processing can involve merging the channel demodulation index sequence and the spurious rearrangement index sequence according to certain logic, generating a unified mapping rule so that the resulting preliminary rearrangement index sequence can simultaneously meet the requirements of target signal fidelity and controllable migration of interfering signals. For example, two sets of index sequences can be integrated according to predetermined logic to resolve position conflicts or overlaps, generating a unified intermediate rearrangement instruction set. Furthermore, a priority mechanism can be adopted to retain valid signal indices that cover spurious indices, or regional mapping can be used to avoid cross-interference, thereby achieving the technical effect of balancing accurate reconstruction of the true target signal and controllable migration of interfering spurious signals.

[0095] Azimuth rearrangement can be based on the actual spatial geometry of a millimeter-wave radar antenna array. It involves angular structural adjustments to the initial rearranged index sequence to ensure the rearranged data conforms to the physical spatial response characteristics, improving the consistency of angle estimation and the reliability of spurious aggregation. For example, azimuth rearrangement can incorporate parameters such as element spacing and topology in the antenna array arrangement to correct the mapping logic of the index sequence in the angular dimension. For instance, index offsets can be corrected by looking up tables based on the array geometry, and azimuth mapping parameters can be optimized through electromagnetic simulation. This achieves matching between the rearrangement strategy and the hardware structure, improving the spatial consistency and engineering feasibility of spurious aggregation effects.

[0096] This embodiment provides a target detection method that obtains a channel demodulation index sequence by performing channel demodulation mapping on an initial data index. This can restore the Doppler shift of the real target caused by phase stepping. Based on the regular distribution of mutual interference spurious signals corresponding to preset waveform parameters and channel demodulation mapping, a spurious rearrangement index sequence specifically used to guide spurious aggregation can be generated. The channel demodulation index sequence and the spurious rearrangement index sequence are fused to obtain a preliminary rearrangement index sequence. Based on the antenna array arrangement of the millimeter-wave radar, the preliminary rearrangement index sequence is rearranged in the azimuth dimension to obtain a preset rearrangement index table. This ensures that the index table adapts to the physical spatial structure, thereby reducing false detection points and improving target detection accuracy as a whole. At the same time, it avoids the running overhead of complex post-processing algorithms, reduces storage and computing resource consumption, and achieves the technical effect of simultaneously optimizing detection accuracy and resource utilization.

[0097] In one embodiment, based on preset waveform parameters, channel demodulation mapping is performed on the initial data index to obtain a channel demodulation index sequence including:

[0098] The phase step value for each transmission channel is determined based on preset waveform parameters;

[0099] The Doppler index offset of the transmit channel is determined based on the phase step value;

[0100] Based on the Doppler index offset of multiple transmission channels, a Doppler index sequence is obtained;

[0101] Based on the Doppler index sequence and the number of receiving channels of the millimeter-wave radar, the channel demodulation index sequence is determined.

[0102] The phase step value can be a discrete increment value introduced by each transmission channel in the phase domain relative to the reference channel. The process of obtaining the phase step value from the preset waveform parameters can refer to the acquisition method in any of the above embodiments, and will not be described in detail here.

[0103] The Doppler index offset can be the theoretical positional shift of the target echo in the Doppler dimension caused by the phase step value of the transmission channel. For example, the phase step value can be converted into a Doppler frequency shift, and then mapped to a discrete index offset value based on the system sampling rate, pulse repetition period, etc., to obtain the Doppler index offset. Furthermore, based on the phase step value, the Doppler index offset of the transmission channel can be determined using methods such as frequency domain phase-frequency conversion formulas or by constructing an offset lookup table based on system calibration parameters, thereby establishing a deterministic mathematical mapping between phase encoding and Doppler position. It can be understood that by determining the Doppler index offset and establishing a deterministic mapping between phase encoding and Doppler position, the responses of the same target in different channels can be predicted and aligned, and the inter-channel offset of the target echo can be accurately predicted.

[0104] A Doppler index sequence can be an ordered set of Doppler index offsets corresponding to multiple transmission channels, used to reflect the theoretically expected Doppler positions of the same target under different transmission channels. In this embodiment, the Doppler index offsets of each transmission channel can be arranged in order of channel number to form a structured index list. Further, the sequence can be obtained by concatenating offset values ​​in order of channel number and / or by normalizing the offset values, thereby constructing a theoretical distribution model of the target in the Doppler domain.

[0105] The number of receiving channels can be the total number of independent receiving antenna channels used to receive echo signals in a millimeter-wave radar system. The channel demodulation index sequence can be a complete mapping sequence constructed based on the Doppler index sequence and the number of receiving channels, used to reposition the original echo data to the correct Doppler position after channel demodulation. In this embodiment, the Doppler index sequence can be extended along the receiving channel dimension, and the index can be copied and aligned in combination with the number of receiving channels to form a unified remapping rule covering all receiving channels, thereby obtaining the channel demodulation index sequence. Furthermore, the Doppler index sequence can be copied and extended along the receiving channel dimension, so that each receiving channel corresponds to a complete Doppler position mapping, forming a unified demodulation index table covering all channels.

[0106] This embodiment provides a target detection method that determines the phase step value of each transmission channel based on preset waveform parameters, determines the Doppler index offset of the transmission channel based on the phase step value, obtains a Doppler index sequence based on the Doppler index offsets of multiple transmission channels, and determines the channel demodulation index sequence based on the Doppler index sequence and the number of receiving channels of the millimeter-wave radar. By converting the phase step value into a Doppler frequency shift and mapping it to a discrete index offset value, a Doppler index sequence reflecting the true echo position of the target is constructed. This sequence is then expanded into a channel demodulation index sequence based on the number of receiving channels, achieving channel-level position correction of multi-channel echo data. This aligns the energy of the same target in the Doppler dimension, transforming the random Doppler misalignment caused by non-equidistant coding into a predictable and reversible index mapping system. Therefore, it determines the distribution pattern of spurious signals from the source and uses it for concentration, avoiding the disorderly diffusion of spurious signals in the Doppler domain. This can significantly reduce the number of false detection points and achieve the technical effect of improving target detection accuracy and system resource utilization.

[0107] In one embodiment, generating a spurious rearrangement index sequence based on the regular distribution of mutual interference spurious signals corresponding to preset waveform parameters and channel demodulation mapping includes:

[0108] Based on the number of receiving channels of the millimeter-wave radar, a preset area is determined; the preset area includes a continuous index interval on the Doppler plane.

[0109] Based on the minimum Doppler offset unit corresponding to the Doppler index offset of multiple transmission channels, the interfering spurious signals are indexed into a preset region to obtain a spurious rearrangement index sequence; wherein, the difference between the Doppler index offsets of any two transmission channels is an integer multiple of the minimum Doppler offset unit.

[0110] The continuous index interval in the Doppler dimension can be an index set consisting of multiple consecutive sampling points in the Doppler dimension, used to accommodate centrally guided spurious signals. Its start and end positions can be determined by system parameters or preset waveform parameters, allowing it to be uniformly shielded or filtered out in subsequent processing. For example, the continuous index interval in the Doppler dimension is calculated based on the number of receiving channels and the minimum Doppler offset unit, ensuring that the interval length can accommodate all spurious energy.

[0111] Furthermore, based on the number of receiving channels of the millimeter-wave radar, determining the preset area can be achieved by calculating the allocatable index range on the Doppler spectrum according to the total number of receiving channels, and setting a continuous index interval as the spurious aggregation target area. Alternatively, based on the number of receiving channels of the millimeter-wave radar, determining the preset area can be achieved by setting the interval length based on the number of receiving channels, and positioning the preset area at the low-frequency, high-frequency, or other concentrated areas of the Doppler spectrum.

[0112] The transmit channel can be an independent channel unit in a millimeter-wave radar used to transmit electromagnetic signals. Since each transmit channel is given a different phase step value to form a MIMO virtual array, a Doppler index offset is generated. In this embodiment, the transmit channels are fixed by the antenna array design, and their number and phase encoding are controlled by preset waveform parameters.

[0113] The minimum Doppler offset unit can be the least common unit of the differences between the Doppler index offsets of multiple transmission channels. It represents the basic interval where spurious signals exhibit a quasi-periodic pattern in the Doppler dimension. Using this as a reference coefficient for the regular distribution of mutually surrounding spurious signals ensures that all spurious energy can be accurately mapped to a predetermined region. For example, the minimum Doppler offset unit can be calculated using preset waveform parameters combined with the antenna array, making it the least common divisor of the Doppler index offset differences between all pairs of transmission channels.

[0114] Spurious signal indexing can be a method of mapping the original position of a spurious signal in the range-Doppler spectrum to an index within a preset region, and periodically aligning it based on the minimum Doppler offset unit, thereby achieving directional migration of spurious energy. In this embodiment, spurious signal indexing can be used to calculate the target offset position of the spurious signal within the preset region based on the relationship between the original position of the spurious signal and the minimum Doppler offset unit.

[0115] Correspondingly, the spurious rearrangement index sequence can be a dedicated mapping sequence generated from the spurious signal index of signals at multiple locations. It is used to indicate the specific location in which each spurious energy point in the range Doppler spectrum should be rearranged to a preset area, so that the spurious signals are concentrated in a fixed frequency band after rearrangement, thereby avoiding the impact on the detection of real weak signal targets.

[0116] Based on the minimum Doppler offset unit corresponding to the Doppler index offset of multiple transmission channels, spurious signals are indexed to a preset region to obtain a spurious rearrangement index sequence. This can be achieved by using the minimum Doppler offset unit as the basic period and mapping the original index of the spurious signal to the corresponding position in the preset region according to its integer multiple relationship with the period, thereby realizing the directional collection of spurious energy.

[0117] In this embodiment, the quasi-periodic pattern of spurious distribution can be such that the difference between the Doppler index offsets of any two transmission channels is an integer multiple of the smallest Doppler offset unit. Therefore, the mathematical modelability of spurious signals can be confirmed, providing a theoretical basis for the generation of spurious rearrangement index sequences.

[0118] This embodiment provides a target detection method that determines a preset region based on the number of receiving channels of a millimeter-wave radar. The preset region includes a continuous index interval in Doppler dimension and a spurious signal index sequence obtained by indexing spurious signals into the preset region based on the minimum Doppler offset unit corresponding to the Doppler index offset of multiple transmitting channels. The difference between the Doppler index offsets of any two transmitting channels is an integer multiple of the minimum Doppler offset unit. By defining a continuous Doppler index interval as the preset region based on the number of receiving channels and using the minimum Doppler offset unit as the mapping reference, all spurious signals are accurately indexed into this region to form a spurious rearrangement index sequence. This can compress spurious energy that is originally diffused in the entire frequency domain into a structured local frequency band, making subsequent target detection less susceptible to the influence of interfering spurious signals and achieving efficient noise suppression. Since no complex filtering or iterative processing is required, but rather false detection points caused by spurious signals are fundamentally eliminated, the detection accuracy can be significantly improved, thereby improving resource utilization.

[0119] In one embodiment, based on the antenna array arrangement of the millimeter-wave radar, the preliminary rearranged index sequence is rearranged in the azimuth dimension to obtain a preset rearranged index table, including:

[0120] Based on the virtual channel physical order corresponding to the antenna array arrangement, the initial rearranged index sequence is re-mapped in the azimuth dimension to obtain a preset rearranged index table.

[0121] The physical order of the virtual channels can be a logical channel sequence derived from the arrangement of the millimeter-wave radar antenna array, which can be used to provide a spatial consistency basis for azimuth rearrangement mapping. Furthermore, the physical order of the virtual channels can be calculated based on the physical coordinates of the transmitting and receiving antennas in the antenna array, using a virtual array synthesis algorithm to calculate the angle sampling points corresponding to each virtual channel, and then arranging them in angular order to form an ordered sequence.

[0122] Azimuth rearrangement mapping can be an index transformation process that repositions data units in the initial rearranged index sequence to their corresponding positions in the angular dimension according to the physical order of the virtual channel. This is used to ensure that the rearranged data conforms to the inherent spatial structure of the physical antenna arrangement in the angular dimension.

[0123] In this embodiment, the preset rearrangement index table can be a complete set of rearrangement rules that is finally solidified after azimuth-dimensional rearrangement mapping. It can be understood that the preset rearrangement index table can be stored in the radar processing unit as a fixed configuration parameter during system operation, or it can be calculated and fixed at any time after the preset waveform parameters are set and before the range Doppler spectrum is acquired.

[0124] This embodiment provides a target detection method that performs azimuth-dimensional rearrangement mapping on a preliminary rearranged index sequence based on the physical order of virtual channels corresponding to the antenna array arrangement, resulting in a preset rearranged index table. By using the physical order of virtual channels as a mapping benchmark, each index item in the preliminary rearranged index sequence is redistributed to a new target position according to the angular order of its corresponding virtual channel, forming the final preset rearranged index table. This method can completely align the rearrangement result with the spatial response characteristics of the physical antenna, achieving high-density aggregation of stray energy in the angular dimension and lossless preservation of the real target structure while ensuring that the distribution of the real target in the angular dimension is not disturbed. This effectively reduces the false alarm rate in subsequent target detection, thereby improving detection accuracy and resource utilization.

[0125] In one embodiment, target detection is performed based on rearranged data, and the target detection results include:

[0126] Perform an azimuth angle Fourier transform on the rearranged data to obtain the Doppler azimuth spectrum;

[0127] The target detection results are obtained by using the constant false alarm rate based on the Doppler azimuth spectrum.

[0128] Among them, the azimuth dimension can be used to describe the distribution dimension of the radar target in the spatial azimuth direction. Together with the range dimension and the Doppler dimension, it constitutes a three-dimensional detection space, which can be used to provide spatial pointing information of the target in the horizontal plane.

[0129] The Doppler azimuth spectrum can be a two-dimensional spectrum obtained by performing a Fourier transform on the rearranged data in the azimuth dimension. It can reflect the joint energy distribution of the target in both the Doppler frequency and azimuth dimensions, thereby enhancing the target's distinguishability in the joint dimension of angle and velocity. In this embodiment, the Doppler azimuth spectrum relies on rearranged data, after which stray energy is concentrated and indexed to a preset region, thus improving the distinguishability between the target and stray energy.

[0130] The Constant False Alarm Rate (CFAR), as an adaptive threshold detection mechanism, dynamically sets the detection threshold by estimating the statistical characteristics of local background noise to maintain a constant false alarm probability. It can be used to suppress false alarms caused by background noise and concentrated stray signals while preserving the ability to detect true targets. For example, the CFAR can employ one or more of the following: cell-average CFAR, ordered statistical CFAR, and lattice CFAR.

[0131] Performing an azimuth angle-dimensional Fourier transform on the rearranged data yields the Doppler azimuth spectrum. This can be achieved by performing a Fast Fourier Transform on the azimuth angle dimension of the rearranged data, converting the spatial domain response into a frequency domain response to form a Doppler-azimuth joint spectrum. This allows for the acquisition of an energy structure with concentrated distribution characteristics in the Doppler-azimuth joint domain, thereby improving detection and discrimination capabilities.

[0132] The constant false alarm rate (CFAR) based on the Doppler azimuth spectrum is used to obtain target detection results. This can be achieved by dynamically calculating the detection threshold for each target unit in the Doppler azimuth spectrum based on the power distribution of its neighboring reference units, and retaining only significant peak values ​​exceeding the threshold as targets. This effectively avoids interfering stray signals that are concentrated in the preset area, prevents them from triggering false alarms, and improves the purity of the detection output.

[0133] This embodiment provides a target detection method that obtains a Doppler azimuth spectrum by performing an azimuth angle-dimensional Fourier transform on rearranged data, and obtains a constant false alarm rate based on the Doppler azimuth spectrum to obtain the target detection result. By forming a structured distribution of stray energy in the Doppler-azimuth joint domain, and utilizing adaptive background estimation capabilities, the method accurately identifies the real target while avoiding known stray aggregation areas. This achieves the technical effect of effectively reducing the false alarm rate and improving detection accuracy and reliability without increasing additional filtering or storage overhead.

[0134] To more clearly illustrate the technical solution of this application, a detailed embodiment is also provided.

[0135] Millimeter-wave radar systems employ various transmit antenna diversity methods. DDMA radar systems, as a type of frequency diversity system, achieve this by adding a phase increment to the transmitted signal within a phase shifter, resulting in a Doppler shift. Different transmit channels have different phase increments. After receiving the signal through the receiving channel, a slow-time FFT is performed. The peak positions of the same target differ across different transmit channels. By utilizing the positional relationship between these peaks, the corresponding transmit channel can be identified, thus enabling transmit channel identification and differentiation.

[0136] Traditional technology provides a way to set the phase step of the transmit channel with completely non-equidistant steps. When setting completely non-equidistant phase step, the intervals between each transmit channel are completely different.

[0137] After signal acquisition, data processing is typically performed using either a Range-Doppler (RD) or Doppler-Azimuth (DA) processing link. The RD processing link sequentially performs range-dimensional and Doppler-dimensional FFT processing on the echo data. Target point detection is then performed on the resulting range-Doppler (RD) domain data matrix, followed by angle calculation based on the target's transmit and receive antenna amplitude and phase values. However, this method only utilizes the non-coherent gain accumulation of the receive channel, not the transmit channel gain accumulation, resulting in limited advantages for detecting weak targets or targets with low signal-to-noise ratios. Weak targets may be submerged in noise and undetectable. The DA processing link, on the other hand, after performing range-dimensional and Doppler-dimensional FFT processing, arranges the MIMO channels according to array element order, performs azimuth-angle-dimensional FFT to achieve coherent angle-dimensional accumulation, and finally processes each range gate bin sequentially. Subsequent target detection and parameter estimation are then performed based on the DA graph of each range gate bin. Compared to the RD processing chain, the DA processing chain has the following advantages: 1. Benefiting from the improved signal-to-noise ratio brought about by 3D coherent accumulation, it is more conducive to weak target detection and has higher parameter estimation accuracy; 2. It strengthens the use of hardware acceleration units, making the signal processing flow more fixed, thereby making the signal processing frame period more stable and the frame latency lower; 3. It has lower memory requirements, can improve the detection range, and output more point clouds.

[0138] However, when combining DDMA waveforms and DA signal processing, MIMO channels need to be rearranged according to their actual array positions during azimuth-angle coherent accumulation. Due to the use of non-equidistant stepping, multiple transmission channels of one target may overlap with those of other targets during MIMO rearrangement, creating multiple spurious signals along the azimuth dimension in the Doppler dimension, thus affecting weak target detection on the DA map. Therefore, minimizing the impact of spurious signals on target detection when applying DDMA waveforms and DA signal processing is a problem that urgently needs to be solved.

[0139] In one embodiment, to address the issue that in DDMA partially non-equally spaced code patterns, the DA signal processing scheme, after performing MIMO channel rearrangement and azimuth angle-dimensional FFT, will generate multiple spurious lines distributed along the angle dimension in the Doppler dimension of the DA graph. These spurious lines will form many CFAR detection points after CFAR detection, not only affecting the screening of normal targets but also causing a huge waste of storage, processor, and time resources. Figure 3 As shown, a target detection method is provided, including the following steps:

[0140] Step S301: Configure preset waveform parameters to enable the transmit channel to transmit a specific DDMA signal.

[0141] Step S302: Perform range dimension and Doppler dimension FFT processing on the acquired ADC data.

[0142] Step S303: Rearrange the Doppler FFT processing results.

[0143] Step S304: Perform azimuth angle dimension FFT on the rearranged signal to generate DA diagram.

[0144] Step S305: Perform CFAR detection on each of the generated DA images to generate a target list.

[0145] In step S301, the Chirp parameters and phase shifter parameters are configured. The Chirp parameters are obtained by the user based on speed and distance specifications; the phase shifter parameters are as follows:

[0146]

[0147] in, N represents the phase increment of the phase shifter in the i-th transmit channel; T The total number of transmitting antennas; i is the transmitting channel number; k i Let be the phase step code coefficient of the i-th transmission channel; This represents the maximum value of the phase step code coefficients; This is the maximum value of the phase step code, i.e., the number of phases supported by the phase shifter; The minimum phase step code interval set by the user, i.e., the minimum phase step code interval, is A positive integer factor of; , , The following relationship must be satisfied:

[0148]

[0149] Therefore, the above formula simplifies to:

[0150]

[0151] Based on the above parameter design, for any two transmission channels i and j, the difference between their phase step values ​​is an integer multiple of a fixed value, that is:

[0152]

[0153] For convenience, the phase step value of transmission channel 1 is set to 0 in this embodiment.

[0154] According to the preset waveform parameters mentioned above, multiple chirps are transmitted, and the transmitted waveforms are as follows: Figure 4 As shown, in the transmission waveform of transmission channel i, the period of each chirp gradually increases to... N c This multiplier creates partially non-equally spaced signals, N c This represents the number of Chirp signals.

[0155] In step S302, for M R The ADC echo data acquired by each receiving channel is first processed using a range-dimensional FFT. Then, a P-point FFT (Doppler-dimensional FFT) is performed on the P chips of each range cell, generating a P×M value. R The data from each cell is used to form a distance Doppler spectrum. The index and arrangement format of each cell are shown in Table 1.

[0156] Table 1. Ranking of data after distance and Doppler FFT

[0157]

[0158] In step S303, the data for each distance cell is rearranged using a rearranged index table to generate data for the azimuth angle dimension FFT. Data rearrangement, i.e., the construction of the rearranged index table, mainly includes three parts: channel demodulation, azimuth dimension rearrangement, and spurious element rearrangement.

[0159] (1) Channel demodulation process.

[0160] Channel demodulation is the process of extracting different MIMO channels of the same target. Based on the aforementioned DDMA waveform, the Doppler index offset Idx of transmit channel i due to phase stepping... Dop-i for:

[0161]

[0162] make ,but .

[0163] For a target with a Doppler index of p, its N T The Doppler index Idx of each transmission channel Dop They are respectively , where mod(p, P) means taking the remainder of p with respect to P.

[0164] If a target has an index of p×M in receive channel 0 R Then all of its N T ×M R The index Idx of each MIMO channel in the data sorting list Dop-MIMO for:

[0165]

[0166] The above formula is for an N T Line, M R A matrix of columns, where each row corresponds to a transmit channel and each column corresponds to a receive channel. It can be written in one-dimensional vector form as follows:

[0167]

[0168] This yields the channel demodulation index sequence Idx' Dop-MIMO :

[0169]

[0170] (2) Orientation rearrangement process.

[0171] Orientation rearrangement is the process of arranging MIMO channel data according to preset array element layout parameters. Let N... T ×M R The element arrangement order of each MIMO channel (i.e., the physical order of the virtual channels) Pos MIMO as follows:

[0172]

[0173] Among them, Pos i Let represent the position of the i-th MIMO channel in the array element arrangement sequence.

[0174] (3) The process of random rearrangement.

[0175] During channel demodulation, the transmission channel of one target may overlap with the transmission channels of other targets, causing its signal to fall onto a channel of another target, forming spurious signals. The arrangement of spurious signals is consistent across different receiving channels; therefore, only the different transmission channels within a single receiving channel need to be considered. As mentioned earlier, for the same receiving channel, the frequency offset Idx of multiple transmission channels due to phase stepping can cause spurious signals. Dop for:

[0176]

[0177] During channel demodulation, the Doppler distribution of spurious emissions from the transmission channel is as follows:

[0178]

[0179] In the above formula, each row represents the spurious location distribution caused by channel demodulation of a transmission channel. For different transmission channels i and j, the difference k of their phase step code coefficients is... i -k j For integers, all stray arrangement indices are ΔIdx. Dop (i.e., an integer multiple of the smallest Doppler cheap unit). Using the above rule, all stray signals of the same target can be rearranged together. The rearranged Doppler index is shown in the following formula:

[0180]

[0181] in, .

[0182] Due to Idx Dop-StrayReshape For Idx Dop-StrayGap The shifted arrangement allows us to generate only Idx. Dop-StrayGap For convenience, the index of a single receiving channel after rearrangement in the above formula is adjusted to the index of the corresponding channel in the data sorting list, resulting in the spurious rearrangement index sequence Idx. Dop-StrayGap :

[0183]

[0184] Combining the above three parts of the rearrangement logic: (1) Channel demodulation Idx' Dop-MIMO (2) Orientational rearrangement Pos MIMO (3) Hidden rearrangement Idx Dop-StrayGap First, based on the channel demodulation index sequence Idx' Dop-MIMO and stray repetition index sequence Idx Dop-StrayGap Generate a preliminary rearranged index sequence IdxDop-Shuffle As shown in the following formula:

[0185]

[0186] Then the initial index sequence Idx is rearranged. Dop-Shuffle Each column of the matrix is ​​rearranged into a sequence Pos according to its orientation dimension. MIMO Arrange them sequentially to generate the final rearranged index table Idx. Dop-ShuffleAll This index table corresponds to one target unit, and the complete lookup table is Idx. Dop-Shuffle Shifted arrangement Idx Dop-ShuffleAll That is, the default rearranged index table:

[0187]

[0188] By rearranging the distance and Doppler FFT-ordered data into a lookup table, the data used for Doppler FFT processing can be obtained.

[0189] It should be noted that the numbering of the above three parts is for distinguishing purposes, not to limit the execution order of the three parts.

[0190] In step S304, an azimuth angle-dimensional FFT is performed on the rearranged signal to generate a DA diagram. Since the azimuth dimension of the rearranged signal is already arranged according to the actual MIMO positions, azimuth-dimensional coherent accumulation (i.e., azimuth-dimensional FFT) can be directly performed. After completing the FFT, the modulus and logarithm of the FFT result are taken to obtain the DA diagram.

[0191] In step S305, CFAR detection is performed on the DA map generated for each distance cell to generate a target list and obtain the target detection results.

[0192] In one specific embodiment, taking a three-transmitter, four-receiver radar system as an example, such as Figure 5 As shown, the functional modules of the radar system include a signal generation module, a signal receiving module, and a signal processing module. The signal generation module controls N transmitting antennas to transmit partially non-equally spaced signals through phase shifters and power amplifiers. M receiving antennas respectively collect data through the signal receiving module, and the data is then processed by the signal processing module. It can be understood that in a three-transmitter, four-receiver radar system, N is 3 and M is 4. The target detection method in this embodiment can be executed by the signal processing module. For example... Figure 6 As shown, in this embodiment of the radar array with three transmitters and four receivers, the transmitting antennas T0, T1, and T2 are spaced 2λ apart, and the receiving antennas R0, R1, R2, and R3 are spaced λ / 2 apart. Figure 6 As shown.

[0193] According to the above scheme, the DDMA waveform parameters are set as follows:

[0194] Table 2 Waveform Configuration Parameters for Signal Generation Module

[0195]

[0196] First, configure the Chirp parameters and phase shifter parameters in the table above to enable the transmit channel to transmit DDMA signals.

[0197] Next, the acquired ADC data is processed by range dimension and Doppler dimension FFT to generate data to be processed by azimuth dimension FFT. The data of each range unit is then processed, and the corresponding receiving channels and their arrangement in memory are shown in Table 3.

[0198] Table 3. Data sorting list for a distance unit

[0199]

[0200] The third step is to rearrange the Doppler FFT processing results. Based on the aforementioned waveform parameters and the waveform parameter table, the spurious interval of the transmission channel is:

[0201]

[0202] The Doppler index offset of the transmit channel due to phase stepping is:

[0203]

[0204] According to the data arrangement format, the corresponding index is:

[0205] ,

[0206]

[0207] Based on the above two equations, we can obtain:

[0208]

[0209]

[0210]

[0211] Based on the array configuration in this embodiment, the MIMO virtual array arrangement order is as follows: Figure 7 As shown, that is: .

[0212] Idx Dop-Shuffle Each column of the matrix, according to Pos MIMO Arranged in sequence, in this embodiment, Pos MIMOThe values ​​are arranged in order, so there is no need to adjust Idx. Dop-Shuffle Based on Idx Dop-Shuffle The final rearranged index lookup table can then be generated, as shown in the following formula:

[0213]

[0214] Based on the aforementioned index lookup table, the data for each distance cell is rearranged to generate data for the azimuth angle dimension FFT. The spurious distribution before and after spurious rearrangement is compared below. Figure 8 As shown, by rearranging the spurious signals, most of the spurious signals are concentrated in the preset area, which can effectively avoid the influence of spurious signals on subsequent target detection.

[0215] Then, perform an azimuth angle FFT on the rearranged signal data, and then calculate the modulus and take the logarithm to obtain the DA diagram.

[0216] Finally, CFAR detection is performed on the DA map generated for each distance cell to generate a target list and obtain the target detection results.

[0217] This embodiment provides a target detection method that employs partially non-equidistant DDMA waveforms and a DA signal processing scheme. Compared to the RD scheme, this method performs three-dimensional coherent signal accumulation, resulting in a lower probability of missing weak targets, higher detection accuracy, and a longer detection range. By utilizing waveform characteristics and a lookup table, channel demodulation, azimuth rearrangement, and spurious rearrangement of data can be completed in a single rearrangement, significantly reducing the hardware resource and processing time requirements of data rearrangement. The spurious rearrangement signal processing scheme can significantly reduce the number of CFAR detection points caused by spurious points, eliminating the burden of a large number of spurious points on target screening, memory usage, and increased processing time.

[0218] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0219] Based on the same inventive concept, this application also provides an apparatus for implementing the method described above. The solution provided by this apparatus is similar to the solution described in the above method; therefore, specific limitations in one or more apparatus embodiments provided below can be found in the limitations of the method described above, and will not be repeated here.

[0220] In one embodiment, such as Figure 9 As shown, this application provides a target detection device for millimeter-wave radar. The target detection device includes a generation module 202, a rearrangement module 204, and a detection module 206, wherein:

[0221] The generation module 202 is used to generate a range Doppler spectrum based on the echo data corresponding to a portion of non-equally spaced signals transmitted based on preset waveform parameters.

[0222] The rearrangement module 204 is used to rearrange the range-Doppler spectrum based on a preset rearrangement index table, so that the interfering spurious signals in the range-Doppler spectrum are concentrated in a preset region to obtain rearranged data. The preset rearrangement index table is determined based on preset waveform parameters and the antenna array arrangement of the millimeter-wave radar.

[0223] The detection module 206 is used to perform target detection based on rearranged data and obtain target detection results.

[0224] In one embodiment, the preset waveform parameters include the minimum phase step code interval and the phase step code coefficient for each transmission channel. The target detection device further includes a control module for: determining the maximum value of the phase step code coefficient based on the minimum phase step code interval and the maximum phase step code value; determining the phase step value for each transmission channel based on the maximum phase step code coefficient and the phase step code coefficient; controlling each transmission channel to transmit a portion of the non-equally spaced signal according to the phase step value; and the difference between the phase step values ​​of any two transmission channels is an integer multiple of a fixed value.

[0225] In one embodiment, the target detection device further includes an index generation module, configured to: perform channel demodulation mapping on the initial data index based on the preset waveform parameters to obtain a channel demodulation index sequence; the channel demodulation index sequence includes the Doppler offset position of the same target under different transmission channels caused by phase stepping; generate a spurious rearrangement index sequence based on the regular distribution of mutual interference spurious signals corresponding to the preset waveform parameters and the channel demodulation mapping; perform fusion processing on the channel demodulation index sequence and the spurious rearrangement index sequence to obtain a preliminary rearrangement index sequence; and perform azimuth rearrangement on the preliminary rearrangement index sequence based on the antenna array arrangement of the millimeter-wave radar to obtain the preset rearrangement index table.

[0226] In one embodiment, the index generation module is further configured to: determine the phase step value of each transmission channel based on the preset waveform parameters; determine the Doppler index offset of the transmission channel based on the phase step value; obtain a Doppler index sequence based on the Doppler index offsets of multiple transmission channels; and determine the channel demodulation index sequence based on the Doppler index sequence and the number of receiving channels of the millimeter-wave radar.

[0227] In one embodiment, the index generation module is further configured to: determine a preset region based on the number of receiving channels of the millimeter-wave radar; the preset region includes a continuous index interval in Doppler dimension; index the interfering spurious signals into the preset region based on the minimum Doppler offset unit corresponding to the Doppler index offsets of multiple transmitting channels, thereby obtaining a spurious rearrangement index sequence; wherein the difference between the Doppler index offsets of any two transmitting channels is an integer multiple of the minimum Doppler offset unit.

[0228] In one embodiment, the index generation module is further configured to: perform azimuth-dimensional rearrangement of the preliminary rearranged index sequence based on the antenna array arrangement of the millimeter-wave radar to obtain the preset rearranged index table, including: performing azimuth-dimensional rearrangement mapping on the preliminary rearranged index sequence based on the virtual channel physical order corresponding to the antenna array arrangement to obtain the preset rearranged index table.

[0229] In one embodiment, the detection module 206 is further configured to: perform target detection based on the rearranged data to obtain the target detection result, including: performing an azimuth angle-dimensional Fourier transform on the rearranged data to obtain a Doppler azimuth spectrum; and performing a constant false alarm rate based on the Doppler azimuth spectrum to obtain the target detection result.

[0230] Each module in the aforementioned target detection device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the operations corresponding to each module.

[0231] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 10As shown, the computer device includes a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a target detection method. The display screen can be an LCD screen or an e-ink display screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device casing, or an external keyboard, touchpad, or mouse.

[0232] Those skilled in the art will understand that Figure 10 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0233] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the target detection method of any of the above embodiments:

[0234] A range Doppler spectrum is generated based on the echo data corresponding to a portion of non-equally spaced signals transmitted according to preset waveform parameters.

[0235] Based on a preset rearrangement index table, the range-Doppler spectrum is rearranged so that the interfering spurious signals in the range-Doppler spectrum are concentrated in a preset region to obtain rearranged data; the preset rearrangement index table is determined based on the preset waveform parameters and the antenna array arrangement of the millimeter-wave radar.

[0236] Target detection is performed based on the rearranged data to obtain the target detection results.

[0237] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the target detection method of any of the above embodiments:

[0238] A range Doppler spectrum is generated based on the echo data corresponding to a portion of non-equally spaced signals transmitted according to preset waveform parameters.

[0239] Based on a preset rearrangement index table, the range-Doppler spectrum is rearranged so that the interfering spurious signals in the range-Doppler spectrum are concentrated in a preset region to obtain rearranged data; the preset rearrangement index table is determined based on the preset waveform parameters and the antenna array arrangement of the millimeter-wave radar.

[0240] Target detection is performed based on the rearranged data to obtain the target detection results.

[0241] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0242] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0243] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0244] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A target detection method, characterized in that, The target detection method, applied to millimeter-wave radar, includes: A range Doppler spectrum is generated based on the echo data corresponding to a portion of non-equally spaced signals transmitted according to preset waveform parameters. Based on a preset rearrangement index table, the range-Doppler spectrum is rearranged so that the interfering spurious signals in the range-Doppler spectrum are concentrated in a preset region to obtain rearranged data; the preset rearrangement index table is determined based on the preset waveform parameters and the antenna array arrangement of the millimeter-wave radar. Target detection is performed based on the rearranged data to obtain the target detection results.

2. The target detection method according to claim 1, characterized in that, The preset waveform parameters include the minimum interval of the phase step code and the phase step code coefficients for each transmission channel. The target detection method further includes: Based on the minimum and maximum phase step codes, the maximum value of the phase step code coefficients is determined. Based on the maximum value of the phase step code coefficient and the phase step code coefficient, the phase step value of each transmission channel is determined; Each of the transmission channels is controlled to transmit partially non-equally spaced signals according to the phase step value; the difference between the phase step values ​​of any two transmission channels is an integer multiple of a fixed value.

3. The target detection method according to claim 1, characterized in that, The preset rearrangement index table is determined based on the preset waveform parameters and the antenna array arrangement of the millimeter-wave radar, including: Based on the preset waveform parameters, channel demodulation mapping is performed on the initial data index to obtain a channel demodulation index sequence; the channel demodulation index sequence includes the Doppler offset position of the same target under different transmission channels due to phase stepping; Based on the preset waveform parameters and the regular distribution of mutual interference spurious signals corresponding to the channel demodulation mapping, a spurious rearrangement index sequence is generated; A preliminary rearranged index sequence is obtained by fusing the channel demodulation index sequence and the spurious rearrangement index sequence. Based on the antenna array arrangement of the millimeter-wave radar, the initial rearranged index sequence is rearranged in the azimuth dimension to obtain the preset rearranged index table.

4. The target detection method according to claim 3, characterized in that, The step of performing channel demodulation mapping on the initial data index based on the preset waveform parameters to obtain the channel demodulation index sequence includes: The phase step value for each transmission channel is determined based on the preset waveform parameters; Based on the phase step value, the Doppler index offset of the transmission channel is determined; Based on the Doppler index offsets of the multiple transmission channels, a Doppler index sequence is obtained; The channel demodulation index sequence is determined based on the Doppler index sequence and the number of receiving channels of the millimeter-wave radar.

5. The target detection method according to claim 4, characterized in that, The step of generating a spurious rearrangement index sequence based on the regular distribution of mutual interference spurious signals corresponding to the preset waveform parameters and the channel demodulation mapping includes: Based on the number of receiving channels of the millimeter-wave radar, a preset area is determined; the preset area includes a continuous index interval on the Doppler plane. Based on the minimum Doppler offset unit corresponding to the Doppler index offset of multiple transmission channels, the interfering spurious signals are indexed into the preset region to obtain a spurious rearrangement index sequence; wherein the difference between the Doppler index offsets of any two transmission channels is an integer multiple of the minimum Doppler offset unit.

6. The target detection method according to claim 3, characterized in that, The antenna array arrangement based on the millimeter-wave radar, and the azimuth-dimensional rearrangement of the preliminary rearranged index sequence to obtain the preset rearranged index table, include: Based on the virtual channel physical order corresponding to the antenna array arrangement, the azimuth dimension rearrangement mapping is performed on the preliminary rearrangement index sequence to obtain a preset rearrangement index table.

7. The target detection method according to claim 1, characterized in that, The target detection based on the rearranged data, resulting in target detection results, includes: Perform an azimuth angle Fourier transform on the rearranged data to obtain the Doppler azimuth spectrum; The target detection result is obtained by performing constant false alarm rate based on the Doppler azimuth spectrum.

8. A target detection device, characterized in that, The target detection device, applied to millimeter-wave radar, includes: The generation module is used to generate a range Doppler spectrum based on the echo data corresponding to a portion of non-equally spaced signals transmitted based on preset waveform parameters. The rearrangement module is used to rearrange the range-Doppler spectrum based on a preset rearrangement index table, so that the interfering spurious signals in the range-Doppler spectrum are concentrated in a preset region to obtain rearranged data; the preset rearrangement index table is determined based on the preset waveform parameters and the antenna array arrangement of the millimeter-wave radar; The detection module is used to perform target detection based on the rearranged data and obtain the target detection result.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 7.

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