Target detection method and device based on millimeter wave radar and control unit

Abstract

The invention provides a target detection method and device based on a millimeter wave radar, and a control unit, and relates to the technical field of radar signal processing. The method comprises the steps that a first thermodynamic diagram corresponding to a detection area of the millimeter wave radar is acquired, the first thermodynamic diagram is divided at equal intervals in the speed dimension, multiple sub-bands are obtained, and the multiple sub-bands comprise a non-empty band and at least two empty bands; performing fusion processing on the plurality of sub-bands to obtain a second thermodynamic diagram; based on a constant false alarm rate algorithm, according to the second thermodynamic diagram, determining a detection point trace corresponding to a real target in the targets; and determining the actual distance and the actual speed of the real target relative to the millimeter wave radar based on the detection trace and according to the phase offset of the transmitting antenna. According to the method, energy in the sub-bands is accumulated in a sub-band segmentation and fusion mode, so that the spectrum peak value of the real target is more prominent, the signal-to-noise ratio of the real target is effectively improved, the probability of occurrence of a false target is reduced, and the target detection precision is improved.

Description

Technical Field

[0001] The present application relates to the field of radar signal processing technology, and in particular to a target detection method, device, and control unit based on millimeter-wave radar. Background Art

[0002] With the increasing popularity of assisted driving systems, millimeter-wave radar, a key component of these systems, is able to accurately identify the position and velocity of targets due to its high frequency and short wavelength. However, vehicles on the road are inevitably subject to various electromagnetic interferences, such as interference from radars on other vehicles, high-voltage power lines, and multipath reflections from the vehicle's own radar. This can cause the noise floor of millimeter-wave radar to rise during target detection, creating false targets. This can lead to false triggering of safety-assisted driving alarms or failure to detect real targets, causing significant inconvenience for the vehicle. Therefore, improving the detection accuracy of millimeter-wave radar is crucial.

[0003] In related technologies, a heat map corresponding to the detection area of a millimeter-wave radar is obtained. A target search is performed on this heat map based on a constant false alarm rate (CFAR) algorithm to obtain target detection results for that detection area. However, this method suffers from low target detection accuracy. Summary of the Invention

[0004] The present application provides a target detection method, device and control unit based on millimeter-wave radar to improve target detection accuracy.

[0005] In a first aspect, the present application provides a target detection method based on millimeter wave radar, comprising:

[0006] Obtaining a first heat map corresponding to a detection area of the millimeter-wave radar, where the first heat map represents a distance and a speed of a target within the detection area relative to the millimeter-wave radar;

[0007] The first heat map is divided into multiple sub-bands at equal intervals along the velocity dimension. The multiple sub-bands include a non-empty band and at least two empty bands. The empty band does not contain a target. The number of non-empty bands is equal to the number of transmitting antennas of the millimeter-wave radar.

[0008] Perform fusion processing on multiple sub-bands to obtain a second heat map;

[0009] Based on the constant false alarm rate algorithm, the detection point trace corresponding to the real target in the target is determined according to the second heat map;

[0010] Based on the detection traces and the phase offset of the transmitting antenna, the actual distance and actual speed of the real target relative to the millimeter wave radar are determined.

[0011] In a possible implementation, multiple sub-bands are fused to obtain a second heat map, including:

[0012] The spectrum peaks corresponding to targets at the same distance in different sub-bands are accumulated to obtain the second heat map.

[0013] In a possible implementation manner, the multiple sub-bands include two empty bands, and / or the constant false alarm rate algorithm includes an ordered statistics constant false alarm rate algorithm.

[0014] In one possible implementation, based on a constant false alarm rate algorithm and according to the second heat map, determining a detection point trace corresponding to a real target in the target includes:

[0015] Based on the constant false alarm rate algorithm, the second heat map is searched for targets in the distance dimension to obtain the distance dimension detection result of the target;

[0016] Based on the constant false alarm rate algorithm, the second heat map is searched for targets in the speed dimension to obtain the speed dimension detection result of the target;

[0017] The coincident target in the distance dimension detection result and the speed dimension detection result is determined as the true target, and the point trace corresponding to the coincident target is determined as the detection point trace corresponding to the true target.

[0018] In one possible implementation, obtaining a first heat map corresponding to a detection area of a millimeter-wave radar includes:

[0019] Obtain radar data corresponding to multiple receiving channels included in the millimeter wave radar. The radar data is generated based on the transmit signal and received echo signal corresponding to the receiving channel;

[0020] Perform two-dimensional Fourier transform processing on the radar data of different receiving channels to obtain the Fourier transform results corresponding to multiple receiving channels;

[0021] Accumulation processing is performed on multiple Fourier transform results to obtain a first thermal map, where the accumulation processing includes coherent accumulation processing or non-correlated accumulation processing.

[0022] In one possible implementation, determining the actual distance and actual speed of the real target relative to the millimeter-wave radar based on the detection trace and the phase offset of the millimeter-wave radar transmitting antenna includes:

[0023] Determine the search range in the distance and velocity dimensions based on the phase offset and the resolution of the millimeter-wave radar;

[0024] Taking each point in the detection trace as a base point, within the search range, according to the phase characteristics of the signal, search for the matching point of the base point in each sub-band;

[0025] Based on the Doppler Division Multiple Access (DDMA) demodulation principle, the target position of the real target in the first thermal map is obtained according to the matching points;

[0026] According to the target position and resolution, the actual distance and actual speed of the real target relative to the millimeter wave radar are determined.

[0027] In a second aspect, the present application provides a target detection device based on millimeter wave radar, comprising:

[0028] An acquisition module is configured to acquire a first thermal map corresponding to a detection area of the millimeter-wave radar, where the first thermal map represents a distance and a speed of a target within the detection area relative to the millimeter-wave radar;

[0029] a segmentation module, configured to segment the first heat map into equal intervals along the velocity dimension to obtain a plurality of sub-bands, wherein the plurality of sub-bands include a non-empty band and at least two empty bands, the empty band does not contain a target, and the number of the non-empty bands is equal to the number of transmitting antennas of the millimeter-wave radar;

[0030] a processing module, configured to perform fusion processing on the multiple sub-bands to obtain a second heat map;

[0031] A first determination module is configured to determine, based on a constant false alarm rate algorithm and according to the second heat map, a detection point trace corresponding to a real target in the target;

[0032] The second determination module is used to determine the actual distance and actual speed of the real target relative to the millimeter wave radar based on the detection point trace and the phase offset of the transmitting antenna.

[0033] In a possible implementation, the processing module is specifically configured to accumulate spectrum peaks corresponding to targets at the same distance in different sub-bands to obtain a second heat map.

[0034] In a possible implementation manner, the multiple sub-bands include two empty bands, and / or the constant false alarm rate algorithm includes an ordered statistics constant false alarm rate algorithm.

[0035] In one possible implementation, the first determination module is specifically used to: perform a target search in the distance dimension on the second heat map based on a constant false alarm rate algorithm to obtain a distance dimension detection result of the target; perform a target search in the speed dimension on the second heat map based on a constant false alarm rate algorithm to obtain a speed dimension detection result of the target; determine the overlapping targets in the distance dimension detection results and the speed dimension detection results as the true targets, and determine the point traces corresponding to the overlapping targets as the detection point traces corresponding to the true targets.

[0036] In one possible embodiment, the acquisition module is specifically used to: obtain radar data corresponding to multiple receiving channels contained in the millimeter-wave radar, where the radar data is generated based on the transmitted signal and the received echo signal corresponding to the receiving channel; perform two-dimensional Fourier transform processing on the radar data of different receiving channels to obtain Fourier transform results corresponding to the multiple receiving channels; and perform accumulation processing on the multiple Fourier transform results to obtain a first thermal map, where the accumulation processing includes coherent accumulation processing or non-correlated accumulation processing.

[0037] In one possible implementation, the second processing module is specifically used to: determine the search range in the distance and speed dimensions based on the phase offset and the resolution of the millimeter-wave radar; take each point in the detection point trace as a base point, and within the search range, search for the matching point of the base point in each sub-band according to the phase characteristics of the signal; based on the DDMA demodulation principle, obtain the target position of the real target in the first thermal map according to the matching point; determine the actual distance and actual speed of the real target relative to the millimeter-wave radar according to the target position and resolution.

[0038] In a third aspect, the present application provides a control unit, comprising: a memory, a processor;

[0039] Memory stores computer-executable instructions;

[0040] The processor executes the computer-executable instructions stored in the memory, so that the processor executes the above first aspect and / or various possible implementations of the first aspect.

[0041] In a fourth aspect, the present application provides a computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are executed by a processor, they are used to implement the first aspect and / or various possible implementation methods of the first aspect as described above.

[0042] In a fifth aspect, the present application provides a computer program product, comprising a computer program, which, when executed by a processor, implements the above first aspect and / or various possible implementations of the first aspect.

[0043] The present application provides a millimeter-wave radar-based target detection method, device, and control unit. The method obtains a first heat map corresponding to the detection area of the millimeter-wave radar, divides the first heat map into equal intervals along the velocity dimension, and obtains multiple subbands, each of which includes a non-empty band and at least two empty bands. The multiple subbands are then fused to obtain a second heat map. Based on the second heat map, a detection point trace corresponding to a true target in the target is determined using a constant false alarm rate algorithm. Based on the detection point trace, the actual distance and actual speed of the true target relative to the millimeter-wave radar are determined according to the phase offset of the transmitting antenna. The present application uses subband segmentation and fusion to accumulate energy in the subbands, making the spectrum peak of the true target more prominent, effectively improving the signal-to-noise ratio of the true target, reducing the probability of false targets, facilitating CFAR algorithm detection, and thus improving target detection accuracy. Fusion of multiple subbands also implements non-coherent secondary accumulation, which can reduce the impact of signal interference or multipath effects and improve the system's anti-interference capability. Furthermore, the reduction in false targets effectively reduces the system's computational load and memory usage. The improvement of signal-to-noise ratio correspondingly increases the maximum detection distance of millimeter-wave radar. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0045] Figure 1 A schematic diagram of a target detection method based on millimeter-wave radar provided in this application;

[0046] Figure 2 Schematic diagram of the process of the target detection method based on millimeter wave radar provided in the embodiment of the present application Figure 1 ;

[0047] Figure 3 Schematic diagram of the process of the target detection method based on millimeter wave radar provided in the embodiment of the present application Figure 2 ;

[0048] Figure 4 This is a schematic diagram of the results of CFAR detection without using the sub-band segmentation and fusion method proposed in an embodiment of the present application;

[0049] Figure 5 This is a schematic diagram of the output result obtained without using the sub-band segmentation and fusion method provided in the embodiment of the present application;

[0050] Figure 6 This is a schematic diagram of the results of CFAR detection using the sub-band segmentation and fusion method proposed in an embodiment of the present application;

[0051] Figure 7A schematic diagram of the output result obtained by using the sub-band segmentation and fusion method provided in an embodiment of the present application;

[0052] Figure 8 A schematic diagram of the structure of a target detection device based on millimeter-wave radar provided in an embodiment of the present application;

[0053] Figure 9 A schematic diagram of the structure of the control unit provided in an embodiment of the present application.

[0054] The above drawings illustrate specific embodiments of the present application, which will be described in more detail below. These drawings and the textual description are not intended to limit the scope of the present application in any way, but rather to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION

[0055] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0056] The terms "first", "second" etc. in the specification and claims of the present application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable in appropriate circumstances, so that the embodiments of the present application described herein can, for example, be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, the process, system, product or equipment comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or that are inherent to these processes, products or equipment.

[0057] In related technologies, millimeter-wave radars are inevitably susceptible to various electromagnetic interferences. This results in false targets in the heat map corresponding to the millimeter-wave radar's detection area often having higher energy (spectral peaks). These false targets are mixed with real targets, making the real targets' spectral peaks less prominent. Furthermore, the increased noise floor reduces the signal-to-noise ratio of real targets, reducing the adjustment range for the CFAR detection threshold. This makes real targets difficult to detect or even creates false targets. These issues ultimately reduce the system's target detection accuracy.

[0058] To solve the above technical problems, the target detection method based on millimeter-wave radar provided in this application divides the first heat map corresponding to the detection area of the millimeter-wave radar into equal intervals in the velocity dimension, and fuses it to form an enhanced second heat map as the detection object of CFAR, effectively improving the signal-to-noise ratio of the real target, reducing the probability of false targets, facilitating CFAR algorithm detection, and thus improving target detection accuracy.

[0059] The following specific embodiments describe in detail the technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0060] Figure 1 This is a schematic diagram of the scenario of the target detection method based on millimeter wave radar provided in this application. Figure 1 As shown, the scenario includes a millimeter-wave radar and multiple targets within its detection range. For example, a millimeter-wave radar is installed in a suitable location on a vehicle for driving assistance. While the vehicle is in motion, the millimeter-wave radar uses the millimeter-wave radar-based target detection method provided in this application to detect targets (obstacles, other vehicles, etc.) around the vehicle. A vehicle may be equipped with multiple millimeter-wave radars, each of which independently executes the millimeter-wave radar-based target detection method provided in this application.

[0061] It should be noted that the execution entity of the millimeter-wave radar-based target detection method provided in this application can be a millimeter-wave radar or a domain controller, such as a vehicle body domain controller. The millimeter-wave radar is used to collect radar data, and the domain controller interacts with the millimeter-wave radar to complete target detection. This application does not impose specific restrictions on the execution entity.

[0062] It should also be noted that the millimeter-wave radar-based target detection method provided in this application can be applied to a variety of fields, not limited to aviation and drones, vehicles, ships, rail transit, agricultural machinery, warehousing and logistics, etc., and this application does not make specific restrictions on this.

[0063] Figure 2 Schematic diagram of the process of the target detection method based on millimeter wave radar provided in the embodiment of the present application Figure 1 ,like Figure 2 As shown, the target detection method includes:

[0064] S201: Obtain a first heat map corresponding to a detection area of a millimeter-wave radar, where the first heat map represents a distance and a speed of a target within the detection area relative to the millimeter-wave radar.

[0065] The first heat map is a two-dimensional range-Doppler spectrum, with one axis representing velocity and the other representing distance. Targets are typically represented as bright spots on the first heat map. The location of these bright spots reflects, to a certain extent, the relationship between the target's range and velocity relative to the millimeter-wave radar (understandably, these distances and speeds are not true relative distances and speeds). Each bright spot corresponds to an intensity value or spectrum peak, representing the target's intensity at that distance and velocity—that is, the target's intensity distribution in the range-velocity space. Noise and interference appear as background signals on the first heat map.

[0066] For example, if the embodiment of this application is executed by a millimeter-wave radar, a processing system may be embedded in the millimeter-wave radar, and the processing system performs relevant processing based on the collected radar data to generate a first heat map. If the embodiment of this application is executed by another domain controller, the millimeter-wave radar is used to collect radar data, and the domain controller interacts with the millimeter-wave radar to obtain radar data from the millimeter-wave radar and generate the first heat map; alternatively, the first heat map can be directly obtained from the millimeter-wave radar.

[0067] It should be noted that due to interference from multipath reflection, high-voltage power lines, other radar signals, etc., the energy of false targets is often high, and the targets on the first heat map may include false targets.

[0068] S202. Divide the first heat map into equal intervals along the velocity dimension to obtain a plurality of sub-bands. The plurality of sub-bands include a non-empty band and at least two empty bands. The empty band does not contain a target. The number of the non-empty bands is equal to the number of transmitting antennas of the millimeter-wave radar.

[0069] It can be understood that multiple sub-bands are sub-areas with the same speed range, each sub-band is still in the form of a distance-speed spectrum, and each sub-band data is a two-dimensional matrix, representing the distance-intensity (peak) information within a specific speed range.

[0070] For example, the value range of the speed axis of the first heat map is [ ] ,in is the maximum speed (absolute value), and a negative value indicates a speed opposite to the reference direction of the millimeter-wave radar. subbands, intervals indicate :

[0071]

[0072] From minimum speed Start with The interval is divided into a plurality of sub-bands.

[0073] In order to achieve subsequent demodulation processing, when performing sub-band division, empty bands need to be set. Empty bands can be regarded as not containing targets and can only contain clutter and noise. The number of non-empty bands is the number of transmitting antennas of the millimeter wave radar (marked as ), then the number of empty bands is For each subband, the speed dimension is reduced to the speed dimension of the first heatmap. , the distance dimension remains scale-invariant.

[0074] S203: Fusing the multiple sub-bands to obtain a second heat map.

[0075] For example, all subband data is accumulated, with each subband representing a different speed range. The fusion process combines the intensity information within these different speed ranges. The fused data can be represented as a new two-dimensional matrix, representing the combined distance-intensity information across all subband speed ranges. This fused data matrix is then used to plot a second heatmap.

[0076] S204: Based on the CFAR algorithm and the second heat map, determine the detection point trace corresponding to the real target in the target.

[0077] Among them, the CFAR algorithm maintains a fixed false alarm rate by dynamically adjusting the detection threshold. It can adaptively adjust the threshold value according to different environmental conditions and background noise levels to ensure detection performance under different signal conditions.

[0078] For example, each point (distance-speed unit) in the second heat map is traversed and regarded as a unit to be detected. The background noise intensity of the reference units around the unit to be detected is calculated according to the CFAR algorithm. The detection threshold is determined based on the background noise intensity and the set false alarm rate. The intensity of the unit to be detected is compared with the detection threshold. If the intensity of the unit to be detected is greater than the detection threshold, it is determined to be a true target. All points determined to be true targets are extracted to form a detection point trace.

[0079] It should be noted that the CFAR algorithm can be a Cell Averaging-CFAR (CA-CFAR) algorithm, a Greatest Of-CFAR (GO-CFAR) algorithm, an Ordered Statistics-CFAR (OS-CFAR) algorithm, or a Variability Index-CFAR (VI-CFAR) algorithm. In practical applications, a suitable CFAR algorithm can be selected based on specific application scenarios and requirements, and this embodiment of the present application does not impose any specific restrictions on this.

[0080] S205: Based on the detection point trace and the phase offset of the transmitting antenna, determine the actual distance and actual speed of the real target relative to the millimeter wave radar.

[0081] The phase offset between transmit antennas is a spatial offset between them, causing signals from different transmit channels to have different phase and amplitude characteristics when received. This offset affects the phase of the target's return signal, which in turn affects distance and speed measurements.

[0082] For example, in an embodiment of the present application, based on the detection point trace and according to the phase offset of the millimeter-wave radar transmitting antenna, determining the actual distance and actual speed of the real target relative to the millimeter-wave radar may specifically include:

[0083] Step S2051: Determine the search range in the distance and speed dimensions based on the phase offset and the resolution of the millimeter wave radar.

[0084] The resolution includes distance resolution and velocity resolution, and the search range is determined by the error introduced by the phase offset and the step size determined by the resolution.

[0085] For example, the range resolution is assumed to be , the velocity resolution is assumed to be , if the distance error introduced by the antenna phase offset is , the velocity error introduced by the antenna phase offset is , then the search range in the distance dimension can be expressed as [- ], the search range in the speed dimension can be expressed as [- ].

[0086] Step S2052: Taking each detection trace as a base point, within the search range, searching for a matching point of the base point in each sub-band according to the phase characteristics of the signal.

[0087] Taking each point in the detection trace as a base point, within the search range determined in step S2051, a search is performed in each subband for a point that best matches the base point, and a matching point is determined for each subband. Matching criteria such as maximum correlation coefficient and minimum phase difference can be used. For example, the correlation coefficient between the phase of each point in the search range and the base point is calculated, and the point with the largest correlation coefficient is selected as the matching point.

[0088] Step S2053: Based on the DDMA demodulation principle and the matching points, the target position of the real target in the first thermal map is obtained.

[0089] DDMA achieves multi-target resolution by assigning different Doppler frequency shifts to different transmitting antennas. The demodulation process of DDMA includes: performing Doppler demodulation on the matching points, restoring the original signal, and determining the target position of the real target in the first thermal map through phase difference or frequency difference ( , ).

[0090] Step S2054: Determine the actual distance and actual speed of the real target relative to the millimeter wave radar based on the target position and resolution.

[0091] For example, the actual distance is equal to , the actual speed is equal to , A calibration item that corrects the actual distance measurement result of the real target. A calibration item used to correct the actual speed measurement results of the real target.

[0092] In the embodiment of the present application, the energy in the sub-bands is accumulated by dividing and fusing the sub-bands, making the spectrum peak of the real target more prominent, enhancing the signal strength, effectively improving the signal-to-noise ratio of the real target, reducing the probability of false targets, facilitating CFAR algorithm detection, and thus improving target detection accuracy. Fusion processing of multiple sub-bands also realizes non-coherent secondary accumulation, which can reduce the impact of signal interference or multipath effects and improve the system's anti-interference ability. In addition, the reduction of false targets effectively reduces the amount of system operations and reduces memory usage. The improvement in signal-to-noise ratio also correspondingly increases the maximum detection range of the millimeter-wave radar.

[0093] In some embodiments, a fusion process is performed on multiple sub-bands to obtain a second heat map, including: accumulating spectrum peaks corresponding to targets at the same distance in different sub-bands to obtain the second heat map.

[0094] For example, the number of subbands is , at a distance of Department, No. Sub-band mid-range The spectrum peak at ,right The same distance in the sub-bands The peak values of the target spectrum are accumulated and can be expressed as .

[0095] It should be noted that, when performing accumulation, it may be simple addition or weighted addition, for example, weighting according to the signal-to-noise ratio of the sub-band.

[0096] In this embodiment, by accumulating the peak values of multiple subbands, the signal-to-noise ratio (SNR) of the target signal can be significantly improved, thereby enhancing target detection capabilities. In environments with strong noise or interference, the accumulation operation can suppress noise, reduce the energy of interfering signals, and improve the reliability of the target signal. This is particularly suitable for multi-target, low SNR applications.

[0097] In some embodiments, the multiple sub-bands include two empty bands, and / or the constant false alarm rate algorithm includes an ordered statistics constant false alarm rate algorithm.

[0098] The number of empty bands affects the computational complexity of the system. The more empty bands there are, the greater the computational complexity and the higher the memory usage. Setting the number of empty bands to 2 effectively reduces the computational complexity of the system while meeting the demodulation requirements.

[0099] In the process of applying the ordered statistical constant false alarm rate algorithm to detect real targets, after calculating the background noise intensity of the reference units around the unit to be detected, these intensity values are sorted, and a certain percentile (for example, 65%) of the sorted intensity values is selected as the estimated value of the background noise; the detection threshold is determined based on the background noise intensity and the set false alarm rate; the intensity of the unit to be detected is compared with the detection threshold; if the intensity of the unit to be detected is greater than the detection threshold, it is determined to be a real target; all points determined to be real targets are extracted to form a detection point trace.

[0100] In radar signal processing, background noise is often non-uniform. Using an ordered statistics constant false alarm rate algorithm can effectively suppress the influence of strong local clutter, maintain a constant false alarm rate, and more accurately estimate the noise level. In multi-target scenarios, where target signals may interfere with each other, using an ordered statistics constant false alarm rate algorithm effectively avoids the influence of neighboring targets on noise estimation, improving the detection accuracy of real targets. Therefore, the ordered statistics constant false alarm rate algorithm performs well in detection accuracy and reliability in non-uniform background noise or multi-target environments, making it more suitable for the application scenarios of the embodiments of the present application.

[0101] In one implementation, the multiple sub-bands include two empty bands, and no restriction is imposed on the constant false alarm rate algorithm.

[0102] In another implementation, the constant false alarm rate algorithm adopts an ordered statistical constant false alarm rate algorithm, and the number of empty bands is greater than 2.

[0103] In another implementation, the number of empty bands is 2, and an ordered statistical constant false alarm rate algorithm is used.

[0104] In some embodiments, based on a constant false alarm rate algorithm, determining the detection point trace corresponding to the real target in the target according to the second heat map may specifically include:

[0105] Step 1.1: Based on the constant false alarm rate algorithm, perform target search in the distance dimension on the second heat map to obtain the distance dimension detection result of the target.

[0106] Step 1.2: Based on the constant false alarm rate algorithm, perform target search in the speed dimension on the second heat map to obtain the speed dimension detection result of the target.

[0107] Step 1.3: Determine the coincident target in the distance dimension detection result and the velocity dimension detection result as the true target, and determine the point trace corresponding to the coincident target as the detection point trace corresponding to the true target.

[0108] It can be understood that for the same target, if both the distance and speed detection results contain the target, it means that the target has been detected in both dimensions, the confidence level is high, and the target is determined to be a true target. In other words, step 1.3 performs a "logical AND" operation on the detection results of the two dimensions to obtain all the true targets included in the second heat map.

[0109] In some embodiments, obtaining a first thermal map corresponding to the detection area of the millimeter-wave radar includes: obtaining radar data corresponding to multiple receiving channels contained in the millimeter-wave radar, the radar data being generated based on the transmitted signal and the received echo signal corresponding to the receiving channel; performing two-dimensional Fourier transform processing on the radar data of different receiving channels to obtain Fourier transform results corresponding to the multiple receiving channels; and performing accumulation processing on the multiple Fourier transform results to obtain the first thermal map, the accumulation processing including coherent accumulation processing or non-correlated accumulation processing.

[0110] Millimeter-wave radar is a multi-input, multi-output radar with multiple transmit antennas and multiple receive antennas, each corresponding to an independent receive channel. The transmit antenna continuously transmits millimeter-wave signals, while the receive antenna picks up echo signals reflected from surrounding targets. For example, if the echo signal received by the first receive channel is a, and the corresponding transmit signal for the first receive channel is b, the radar data generation process can be as follows: echo signal a and transmit signal b are first mixed and filtered (analog signals), and then further processed by an analog-to-digital converter (ADC) to generate ADC data, i.e., radar data.

[0111] The radar data of each receiving channel is processed by two-dimensional Fourier transform. For example, if there are 6 receiving channels, 6 Fourier transform results are obtained. Each Fourier transform result represents the spatial distribution of the target in the range-Doppler (velocity) plane.

[0112] For example, the accumulation of six Fourier transform results can be implemented in the following two ways:

[0113] One implementation method is to perform modulo summation on the Fourier transform results of the six receiving channels to achieve non-coherent accumulation processing.

[0114] Another implementation method is to first phase-align multiple Fourier transform results and then accumulate them under the phase-aligned condition to ensure that the phases of all Fourier transform results are consistent and avoid phase randomization that leads to a decrease in the accumulation effect.

[0115] In an embodiment of the present application, by performing two-dimensional FFT processing and accumulation on the ADC data of multiple receiving channels, a range-Doppler heat map with a high signal-to-noise ratio can be generated, which significantly improves the target detection capability and is suitable for various scenarios such as automotive radar and airborne radar.

[0116] Figure 3 Schematic diagram of the process of the target detection method based on millimeter wave radar provided in the embodiment of the present application Figure 2 ,like Figure 3 As shown, this embodiment further illustrates a target detection method based on millimeter wave radar based on the above embodiment, and the method includes:

[0117] S301: Perform FFT processing on radar data corresponding to multiple receiving channels included in the millimeter wave radar.

[0118] For example, two-dimensional FFT processing is performed on the ADC data collected by each receiving channel to obtain an FFT result corresponding to each receiving channel.

[0119] S302: Accumulate the FFT results of all receiving channels to form a first heat map corresponding to the detection area of the millimeter-wave radar.

[0120] The FFT results of each receiving channel are modulo-accumulated to achieve non-coherent accumulation processing and generate a first thermal map.

[0121] Alternatively, multiple FFT results can be phase-aligned first and then accumulated under the phase-aligned condition to generate the first heat map. This ensures that the phases of all FFT results are consistent to avoid phase randomization that may lead to a decrease in the accumulation effect.

[0122] The first heat map is a two-dimensional range-Doppler spectrum, with one axis representing speed and the other representing distance. The target is usually represented as a bright spot on the first heat map. The position of the bright spot reflects, to a certain extent, the relationship between the target's distance and speed relative to the millimeter-wave radar (it is understood that this distance and speed are not the actual relative distance and relative speed).

[0123] S303 : Divide the first heat map into equal intervals in the speed dimension to obtain multiple sub-bands.

[0124] For example, the first heat map is divided into A sub-band, is the number of transmitting antennas of the millimeter-wave radar, and 2 is the number of empty bands.

[0125] S304: Accumulate data of multiple sub-bands to form a second heat map.

[0126] It can effectively improve the signal-to-noise ratio of the real target, making its peak more prominent and easier to detect CFAR. At the same time, it can reduce the energy of the interference signal to a certain extent.

[0127] S305: Perform CFAR detection on the second heat map to obtain detection point traces corresponding to the real target in the target.

[0128] For example, based on the OS-CFAR algorithm, the second heat map is searched for targets in both the distance and speed dimensions, obtaining target detection results in the distance and speed dimensions. The detection results in the two dimensions are then merged, specifically using a "logical AND" operation, to obtain all true targets contained in the second heat map.

[0129] S306: Based on the detection point trace and the phase offset of the transmitting antenna, determine the actual distance and actual speed of the real target relative to the millimeter wave radar.

[0130] Taking the detection point trace as the demodulation base point, the matching point corresponding to the base point is searched in each sub-band according to the phase offset of the transmitting antenna. Based on the DDMA demodulation principle, the position of the first transmitting channel on the first heat map is demodulated according to the matching point, and the distance point and velocity point of its location are recorded. The relative distance and velocity of the real target and the radar are calculated using the resolution of distance and velocity.

[0131] Next, in order to verify the effectiveness of the target detection method based on millimeter-wave radar proposed in this application, the method proposed in this application was verified using real road data.

[0132] In the test scenario, the target moves away from the millimeter-wave radar at a speed of 2m / s. Figure 4 This is a schematic diagram of the results of CFAR detection without using the sub-band segmentation and fusion method proposed in the embodiment of the present application. Figure 5 This is a schematic diagram of the output results obtained without using the sub-band segmentation and fusion method provided in the embodiment of the present application.

[0133] like Figure 4 As shown, the horizontal axis x represents distance, and the vertical axis Y represents speed. Figure 4 It can be regarded as the detection result obtained by performing CFAR detection directly based on the first heat map in the above embodiment. It can be seen that the target has many traces (distributed points in the figure) in each sub-band of the CFAR detection result. After matching demodulation, the final display interface ( Figure 5 ) there will be a phenomenon where false targets and real targets coexist, and the speed of the false targets is relatively large. Figure 5 The (0,0) coordinate on (a) and (b) represents the millimeter wave radar. One of the two targets shown is a false target and the other is a real target. Figure 5 (a) can reflect the position distribution of the target relative to the millimeter wave radar. Figure 5 (b) reflects the distance and velocity distribution of the target relative to the millimeter-wave radar.

[0134] Without knowing the true speed, the system has difficulty determining which is the real target. In the case of severe interference or strong multipath effects, the number and probability of false targets will increase significantly, seriously affecting driving safety.

[0135] Figure 6 This is a schematic diagram of the results of CFAR detection using sub-band segmentation and fusion proposed in an embodiment of the present application. Figure 7 This is a schematic diagram of the output results obtained by using the sub-band segmentation and fusion method provided in an embodiment of the present application.

[0136] like Figure 6 As shown, the horizontal axis x represents distance, and the vertical axis Y represents speed. Figure 6 The CFAR detection results for 6 sub-bands and 2 empty bands are shown in Figure 2. As can be seen, after accumulating multiple sub-bands, the peak value of the target is increased due to the re-accumulation of energy. The CFAR detection results of the first sub-band have fewer traces and the number of false points is reduced. After matching demodulation, the final display interface ( Figure 7 ), only one valid target point (real target) is obtained, and its speed (2m / s) is consistent with that of the real target.

[0137] The above experiments verify the effectiveness of the target detection method based on millimeter-wave radar provided in this application.

[0138] In summary, this application has at least the following advantages:

[0139] First, by segmenting and fusing subbands, the energy within the subbands is accumulated, making the spectrum peaks of true targets more prominent, enhancing signal strength, and effectively improving the signal-to-noise ratio of true targets. This reduces the probability of false targets, facilitates CFAR detection, and thus improves target detection accuracy. Fusion of multiple subbands also implements non-coherent secondary accumulation, which reduces the impact of signal interference and multipath effects and improves the system's anti-interference capability.

[0140] Second, the reduction of false targets effectively reduces the system's computational workload and memory usage. The improvement in signal-to-noise ratio also increases the maximum detection range of millimeter-wave radar.

[0141] 3. By performing two-dimensional FFT processing and accumulation on the ADC data of multiple receiving channels, a high signal-to-noise ratio range-Doppler heat map can be generated, significantly improving target detection capabilities. It is suitable for various scenarios such as automotive radar and airborne radar.

[0142] Figure 8 This is a schematic diagram of the structure of the target detection device based on millimeter wave radar provided in the embodiment of the present application, as shown in FIG. Figure 8 As shown, the target detection device 80 based on millimeter wave radar provided in this embodiment includes: an acquisition module 81, a segmentation module 82, a processing module 83, a first determination module 84 and a second determination module 85. Among them:

[0143] An acquisition module 81 is configured to acquire a first thermal map corresponding to a detection area of the millimeter-wave radar, where the first thermal map represents a distance and a speed of a target within the detection area relative to the millimeter-wave radar.

[0144] a segmentation module 82 configured to segment the first heat map into equal intervals along the velocity dimension to obtain a plurality of sub-bands, wherein the plurality of sub-bands includes a non-empty band and at least two empty bands, the empty band does not contain a target, and the number of the non-empty bands is equal to the number of transmitting antennas of the millimeter-wave radar;

[0145] A processing module 83 is configured to perform fusion processing on the multiple sub-bands to obtain a second heat map;

[0146] A first determination module 84 is configured to determine, based on a constant false alarm rate algorithm and according to the second heat map, a detection point trace corresponding to a real target in the target;

[0147] The second determination module 85 is configured to determine the actual distance and actual speed of the real target relative to the millimeter wave radar based on the detection point trace and the phase offset of the transmitting antenna.

[0148] In a possible implementation, the processing module 83 is specifically configured to accumulate spectrum peaks corresponding to targets at the same distance in different sub-bands to obtain a second heat map.

[0149] In a possible implementation manner, the multiple sub-bands include two empty bands, and / or the constant false alarm rate algorithm includes an ordered statistics constant false alarm rate algorithm.

[0150] In one possible implementation, the first determination module 84 is specifically used to: perform a target search in the distance dimension on the second heat map based on a constant false alarm rate algorithm to obtain a distance dimension detection result of the target; perform a target search in the speed dimension on the second heat map based on a constant false alarm rate algorithm to obtain a speed dimension detection result of the target; determine the overlapping targets in the distance dimension detection results and the speed dimension detection results as the true targets, and determine the point traces corresponding to the overlapping targets as the detection point traces corresponding to the true targets.

[0151] In one possible embodiment, the acquisition module 81 is specifically used to: obtain radar data corresponding to multiple receiving channels contained in the millimeter-wave radar, where the radar data is generated based on the transmitted signal and the received echo signal corresponding to the receiving channel; perform two-dimensional Fourier transform processing on the radar data of different receiving channels to obtain Fourier transform results corresponding to the multiple receiving channels; and perform accumulation processing on the multiple Fourier transform results to obtain a first thermal map, where the accumulation processing includes coherent accumulation processing or non-correlated accumulation processing.

[0152] In one possible implementation, the second processing module 85 is specifically used to: determine the search range in the distance and speed dimensions based on the phase offset and the resolution of the millimeter-wave radar; take each point in the detection point trace as a base point, and within the search range, search for the matching point of the base point in each sub-band according to the phase characteristics of the signal; based on the DDMA demodulation principle, obtain the target position of the real target in the first thermal map according to the matching point; determine the actual distance and actual speed of the real target relative to the millimeter-wave radar according to the target position and resolution.

[0153] The target detection device based on millimeter-wave radar provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effects are similar, and are not described in detail in this embodiment.

[0154] Figure 9 This is a schematic diagram of the structure of the control unit provided in the embodiment of the present application. Figure 9 As shown, the control unit 90 provided in this embodiment includes: at least one processor 901 and a memory 902. Optionally, the control unit 90 also includes a communication component 903. The processor 901, the memory 902, and the communication component 903 are connected via a bus 904.

[0155] During the specific implementation process, at least one processor 901 executes the computer-executable instructions stored in the memory 902, so that the at least one processor 901 performs the above method.

[0156] The specific implementation process of the processor 901 can be found in the above method embodiment. Its implementation principle and technical effects are similar and will not be repeated here in this embodiment.

[0157] In the above embodiments, it should be understood that the processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASICs), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the present invention may be directly executed by a hardware processor or by a combination of hardware and software modules within the processor.

[0158] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage.

[0159] A bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. Buses can be categorized as address buses, data buses, and control buses. For ease of illustration, the buses in the drawings of this application are not limited to just one bus or just one type of bus.

[0160] An embodiment of the present application also provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0161] An embodiment of the present application further provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above-mentioned method is implemented.

[0162] The readable storage medium may be implemented by any type of volatile or non-volatile memory device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium may be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0163] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be an integral part of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0164] The division of units is merely a logical functional division; actual implementations may employ alternative divisions, such as combining or integrating multiple units or components into another system, or omitting or disabling certain features. Furthermore, any direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between devices or units, either through an interface, electrical, mechanical, or other means.

[0165] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0166] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0167] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the method of the present invention. The aforementioned storage medium includes various media that can store program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0168] Those skilled in the art will appreciate that all or part of the steps in the above-described method embodiments can be implemented using hardware associated with program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0169] Finally, it should be noted that those skilled in the art will readily identify other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses, or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art not disclosed herein. The present invention is not limited to the precise structure described above and illustrated in the accompanying drawings, and various modifications and variations may be made without departing from the scope thereof. The scope of the present invention is limited solely by the appended claims.

Claims

1. A target detection method based on millimeter wave radar, characterized in that: include: Obtaining a first heat map corresponding to a detection area of the millimeter-wave radar, where the first heat map represents a distance and a speed of a target within the detection area relative to the millimeter-wave radar; Divide the first heat map into equal intervals along the velocity dimension to obtain a plurality of sub-bands, wherein the plurality of sub-bands include a non-empty band and at least two empty bands, the empty band does not contain a target, and the number of the non-empty bands is the number of transmitting antennas of the millimeter-wave radar; Performing a fusion process on the multiple sub-bands to obtain a second heat map; Determining, based on the second heat map and based on a constant false alarm rate algorithm, a detection point trace corresponding to a real target in the target; Based on the detection point trace and according to the phase offset of the transmitting antenna, the actual distance and actual speed of the real target relative to the millimeter wave radar are determined.

2. The target detection method according to claim 1, wherein: The fusing the multiple sub-bands to obtain a second heat map includes: The spectrum peaks corresponding to the targets at the same distance in different sub-bands are accumulated to obtain the second heat map.

3. The target detection method according to claim 2, wherein: The multiple sub-bands include two empty bands, and / or the constant false alarm rate algorithm includes an ordered statistical constant false alarm rate algorithm.

4. The target detection method according to any one of claims 1 to 3, characterized in that: The method of determining, based on the constant false alarm rate algorithm and according to the second heat map, a detection point trace corresponding to a real target in the target includes: Based on the constant false alarm rate algorithm, performing target search in the distance dimension on the second heat map to obtain a distance dimension detection result of the target; Based on the constant false alarm rate algorithm, performing a target search in the speed dimension on the second heat map to obtain a speed dimension detection result of the target; The coincident target in the distance dimension detection result and the speed dimension detection result is determined as the true target, and the point trace corresponding to the coincident target is determined as the detection point trace corresponding to the true target.

5. The target detection method according to any one of claims 1 to 3, characterized in that: The obtaining of a first thermal map corresponding to the detection area of the millimeter wave radar includes: Acquire radar data corresponding to each of a plurality of receiving channels included in the millimeter-wave radar, where the radar data is generated based on a transmit signal and a received echo signal corresponding to the receiving channel; Performing two-dimensional Fourier transform processing on the radar data of different receiving channels to obtain Fourier transform results corresponding to the multiple receiving channels respectively; Accumulation processing is performed on the multiple Fourier transform results to obtain the first thermal map, and the accumulation processing includes coherent accumulation processing or non-correlated accumulation processing.

6. The target detection method according to any one of claims 1 to 3, characterized in that: The determining, based on the detection point trace and according to the phase offset of the millimeter-wave radar transmitting antenna, the actual distance and actual speed of the real target relative to the millimeter-wave radar includes: Determining a search range in distance and speed dimensions according to the phase offset and the resolution of the millimeter-wave radar; Taking each of the detection traces as a base point, searching for a matching point of the base point in each of the sub-bands according to a phase characteristic of a signal within the search range; Based on the Doppler division multiple access (DDMA) demodulation principle, obtaining the target position of the real target in the first thermal map according to the matching point; The actual distance and actual speed of the real target relative to the millimeter wave radar are determined according to the target position and the resolution.

7. A target detection device based on millimeter wave radar, characterized in that: include: an acquisition module, configured to acquire a first heat map corresponding to a detection area of the millimeter-wave radar, wherein the first heat map represents a distance and a speed of a target within the detection area relative to the millimeter-wave radar; a segmentation module, configured to perform equal-interval segmentation on the first heat map in a velocity dimension to obtain a plurality of sub-bands, wherein the plurality of sub-bands include a non-empty band and at least two empty bands, the empty bands do not contain targets, and the number of the non-empty bands is the number of transmitting antennas of the millimeter-wave radar; a processing module, configured to perform fusion processing on the multiple sub-bands to obtain a second heat map; A first determination module is configured to determine, based on a constant false alarm rate algorithm and according to the second heat map, a detection point trace corresponding to a real target in the target; The second determination module is used to determine the actual distance and actual speed of the real target relative to the millimeter wave radar based on the detection point trace and the phase offset of the transmitting antenna.

8. A control unit, characterized in that: include: Memory, processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor performs the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 6 when executed.

10. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 6 when the computer program is executed.

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