False detection point determination method and device, storage medium and electronic device

Abstract

This application discloses a method, apparatus, storage medium, and electronic device for determining false detection points. The method includes: determining a set of points based on the echo signal of a target radar system; if the set of points includes strong reflection points, determining a subset of candidate points associated with the strong reflection points from the set of points; if a first distance index value of the strong reflection point and a second distance index value of at least one candidate point in the subset of candidate points satisfy an index difference condition, and the echo energy difference between at least one candidate point and the strong reflection point satisfies an energy threshold condition, determining the point state of at least one candidate point; and if at least one candidate point is in motion, determining a false detection point from the at least one candidate point. This application solves the technical problem of low efficiency in determining false detection points in related technologies.

Description

Technical Field

[0001] This application relates to the field of autonomous driving, and more specifically, to a method, apparatus, storage medium, and electronic device for determining false detection points. Background Technology

[0002] In intelligent transportation systems and autonomous vehicles, millimeter-wave radar serves as a crucial environmental perception sensor, its performance impacting system decision-making and safety. In multiple-input multiple-output (MIMO) radar architectures, the use of Doppler multiple access (DDMA) waveforms can enhance the radar's target detection capabilities and the accuracy of parameter estimation. However, in practical deployments, DDMA MIMO radar systems encounter phase shifter misalignment issues caused by factors such as manufacturing tolerances of hardware, environmental temperature variations, and non-ideal component matching.

[0003] To address the false alarm problem caused by phase shifter phase offset, existing technologies for each detected target point trace traverse all points with the same distance index value to extract the Doppler spectrum associated with that point trace. The corresponding amplitude values ​​are then extracted at fixed intervals, and all amplitude values ​​are summed to obtain a judgment threshold, thereby filtering out false detection points. In other words, existing technologies suffer from low efficiency in identifying false detection points due to phase shifter phase offset. Summary of the Invention

[0004] This application provides a method, apparatus, storage medium, and electronic device for determining false detection points, so as to at least solve the technical problem of low efficiency in determining false detection points in related technologies.

[0005] According to one aspect of the embodiments of this application, a method for determining false detection points is provided, comprising: determining a set of points based on the echo signal of a target radar system, wherein the set of points includes multiple point objects; when the set of points includes strong reflection points, determining a subset of candidate points associated with the strong reflection points from the set of points, wherein the point distance between the candidate points in the subset of candidate points and the strong reflection points satisfies a target distance condition; determining the point state of at least one candidate point when a first distance index value of the strong reflection point and a second distance index value of at least one candidate point in the subset of candidate points satisfy an index difference condition, and the echo energy difference between at least one candidate point and the strong reflection point satisfies an energy threshold condition; and determining false detection points from at least one candidate point when at least one candidate point is in motion.

[0006] According to another aspect of the embodiments of this application, a device for determining false detection points is also provided, comprising: a first determining unit for determining a set of points based on the echo signal of a target radar system, wherein the set of points includes multiple point objects; a second determining unit for determining a subset of candidate points associated with strong reflection points from the set of points when the set of points includes strong reflection points, wherein the point distance between the candidate points in the subset of candidate points and the strong reflection points satisfies a target distance condition; a third determining unit for determining the point state of at least one candidate point when the first distance index value of the strong reflection point and the second distance index value of at least one candidate point in the subset of candidate points satisfy an index difference condition, and the echo energy difference between at least one candidate point and the strong reflection point satisfies an energy threshold condition; and a fourth determining unit for determining false detection points from at least one candidate point when at least one candidate point is in motion.

[0007] As an optional solution, the third determining unit further includes: a state determining module, used to determine the difference between the first distance index value of the strong reflection point and the second distance index value of at least one candidate point, to obtain a distance index difference; if the absolute value of the distance index difference is less than the first difference threshold, to determine the difference between the echo energy value of the strong reflection point and the echo energy value of the candidate point, to obtain an echo energy difference; if the echo energy difference is greater than the first energy threshold, to determine the point state of the candidate point.

[0008] As an optional solution, the aforementioned state determination module includes: a first acquisition module, used to acquire a first velocity index value of a strong reflection point and a second velocity index value of a current candidate point, and calculate the velocity index difference between the first velocity index value and the second velocity index value; if the velocity index difference satisfies the target interval condition, the current candidate point is determined as a false detection point, wherein the target interval condition is determined according to the waveform parameters of the target radar system.

[0009] As an optional solution, the first acquisition module is further used to determine the current candidate point as a false detection point if the velocity index difference between the first velocity index value and the second velocity index value satisfies the condition that the phase offset difference in the waveform parameters of the target radar system is an integer multiple.

[0010] As an optional scheme, the second determining unit is also used to determine the serial number of the strong reflection point in the point information list, wherein the point information list is obtained by sorting the point objects in the point set according to the radial distance index value distribution; if the serial number interval between at least one reference point and the strong reflection point in the point information list is less than or equal to the serial number interval threshold, at least one reference point is determined as a candidate point.

[0011] As an optional solution, the second determining unit further includes a second acquisition module, used to acquire the echo energy value of the trace object in the trace set; acquire the distance index value of the trace object when the echo energy value is greater than the second energy threshold; and determine the trace object as a strong reflective trace when the distance index value is less than the target sample acquisition value.

[0012] According to another aspect of the embodiments of this application, a computer program product or computer program is provided, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the method for determining false detection points as described above.

[0013] According to another aspect of the embodiments of this application, an electronic device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the above-described method for determining false detection points through the computer program.

[0014] Through the above-described embodiments of this application, a set of point tracks is determined based on the echo signal of the target radar system. When the set of point tracks includes strong reflection point tracks, a subset of candidate point tracks associated with the strong reflection point tracks is determined from the set of point tracks. The point track distances between the candidate point tracks in the subset of candidate point tracks and the strong reflection point tracks satisfy the target distance condition, quickly locating areas potentially affected by phase shifter phase deviations, thus avoiding a comprehensive analysis of the entire set of point tracks. Furthermore, when the first distance index value of the strong reflection point track and the second distance index value of at least one candidate point track in the subset of candidate point tracks satisfy the index difference condition, and the echo energy difference between at least one candidate point track and the strong reflection point track satisfies the energy threshold condition, the point track state of at least one candidate point track is determined. This achieves the determination of false detection point tracks from at least one candidate point track even when at least one candidate point track is in motion, thereby solving the technical problem of low efficiency in determining false detection point tracks in related technologies. Attached Figure Description

[0015] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0016] Figure 1 This is a schematic diagram of the application environment of an optional method for determining false detection points according to an embodiment of this application;

[0017] Figure 2 This is a flowchart of an optional method for determining false detection points according to an embodiment of this application;

[0018] Figure 3 This is a schematic diagram of an optional radial distance index value-radial relative velocity index value according to an embodiment of this application;

[0019] Figure 4 This is an optional dot filtering diagram according to an embodiment of this application;

[0020] Figure 5 This is another optional dot filtering diagram according to an embodiment of this application;

[0021] Figure 6 This is another optional dot filtering diagram according to an embodiment of this application;

[0022] Figure 7 This is a flowchart of another optional method for determining false detection points according to an embodiment of this application;

[0023] Figure 8 This is a flowchart of another optional method for determining false detection points according to an embodiment of this application;

[0024] Figure 9 This is a schematic diagram of a device for determining false detection marks according to an embodiment of this application;

[0025] Figure 10 This is a schematic diagram of the structure of an optional electronic device according to an embodiment of this application. Detailed Implementation

[0026] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0027] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0028] According to one aspect of the embodiments of this application, a method for determining false detection points is provided. Optionally, the method for determining false detection points can be applied, but is not limited to, to applications such as... Figure 1 The hardware environment shown. Optionally, the method for determining false detection points provided in this application can be applied to a vehicle terminal. Figure 1 A side view of a vehicle terminal 101 is shown, which can travel on a driving surface 113. The vehicle terminal 101 includes a memory 102 storing an onboard navigation system 103 and a digital road map 104, a spatial monitoring system 117, a vehicle controller 109, a GPS (Global Positioning System) sensor 110, an HMI (Human / Machine Interface) device 111, and also includes an autonomous controller 112 and a telematics controller 114.

[0029] In one embodiment, the space monitoring system 117 includes one or more space sensors and systems for monitoring a visible area 105 in front of the vehicle terminal 101. The space monitoring system 117 also includes a space monitoring controller 118. The space sensors for monitoring the visible area 105 include a lidar sensor 106, a radar sensor 107, a camera 108, etc. The space monitoring controller 118 can be used to generate data related to the visible area 105 based on data input from the space sensors. The space monitoring controller 118 can determine the linear range, relative speed, and trajectory of the vehicle terminal 101 based on the input from the space sensors, for example, determining the vehicle's current speed and its relative speed to a vehicle in front. The space sensors of the vehicle terminal space monitoring system 117 may include object positioning sensing devices, which may include range sensors that can be used to locate objects in front, such as vehicles in front.

[0030] Camera 108 is advantageously mounted and positioned on vehicle terminal 101 in a location that allows for the capture of images of a visible area 105, wherein at least a portion of the visible area 105 includes the area in front of vehicle terminal 101 and a portion of the travel surface 113 of the trajectory of vehicle terminal 101. The visible area 105 may also include the surrounding environment. Other cameras may also be employed, for example, including a second camera positioned on the rear or side portion of vehicle terminal 101 to monitor the rear of vehicle terminal 101 and one of the right or left sides of vehicle terminal 101.

[0031] The autonomous controller 112 is configured to implement autonomous driving or advanced driver assistance system (ADAS) vehicle terminal functionality. Such functionality may include an onboard vehicle terminal control system capable of providing a certain level of driving automation. Driving automation may include a series of dynamic driving and vehicle terminal operations. Driving automation may include a certain level of automated control or intervention involving individual vehicle terminal functions (e.g., steering, acceleration, and / or braking). For example, the aforementioned autonomous controller and the aforementioned radar sensor can be used to determine false detection points by performing the following steps:

[0032] S102, determine the set of points based on the echo signal of the target radar system, wherein the set of points includes multiple point objects;

[0033] S104, if the set of points includes strongly reflective points, determine a subset of candidate points associated with the strongly reflective points from the set of points, wherein the point distance between the candidate points in the subset of candidate points and the strongly reflective points satisfies the target distance condition.

[0034] S106, if the first distance index value of the strong reflection point trace and the second distance index value of at least one candidate point trace in the candidate point trace subset satisfy the index difference condition, and the echo energy difference between at least one candidate point trace and the strong reflection point trace satisfies the energy threshold condition, determine the point trace state of at least one candidate point trace.

[0035] S108, when at least one candidate point is in motion, determine the false detection point from at least one candidate point.

[0036] HMI device 111 provides human-machine interaction for guiding the operation of infotainment systems, GPS (Global Positioning System) sensors 110, airborne navigation systems 103, and similar systems, and includes controllers. HMI device 111 monitors operator requests and provides the operator with status, service, and maintenance information about the vehicle terminal system. HMI device 111 communicates with and / or controls the operation of multiple operator interface devices. HMI device 111 may also communicate with one or more devices that monitor biometric data associated with the vehicle terminal operator. For simplicity, HMI device 111 is depicted as a single device, but in embodiments of the system described herein, it may be configured as multiple controllers and associated sensing devices.

[0037] Operator controls may be included in the passenger compartment of vehicle terminal 101, and by way of non-limiting example, may include a steering wheel, accelerator pedal, brake pedal, and operator input device, which is an element of HMI device 111. The operator controls enable a vehicle terminal operator to interact with and instruct the operation of vehicle terminal 101 to provide passenger transport.

[0038] The airborne navigation system 103 uses a digital road map 104 for the purpose of providing navigation support and information to the vehicle terminal operator. The autonomous controller 112 uses the digital road map 104 for the purpose of controlling the operation of the autonomous vehicle terminal or the functions of the ADAS vehicle terminal.

[0039] The vehicle terminal 101 may include a telematics controller 114, which includes a wireless telematics communication system capable of external communication (including communication with a communication network 115 with both wireless and wired communication capabilities). The wireless telematics communication system includes a non-airborne server 116 capable of short-range wireless communication with mobile terminals.

[0040] As an optional implementation method, such as Figure 2 As shown, the method for determining false detection points can be performed by an electronic device, and the specific steps include:

[0041] S202, determine the set of points based on the echo signal of the target radar system, wherein the set of points includes multiple point objects;

[0042] S204, if the set of points includes strongly reflective points, determine a subset of candidate points associated with the strongly reflective points from the set of points, wherein the point distance between the candidate points in the subset of candidate points and the strongly reflective points satisfies the target distance condition.

[0043] S206, if the first distance index value of the strong reflection point trace and the second distance index value of at least one candidate point trace in the candidate point trace subset satisfy the index difference condition, and the echo energy difference between at least one candidate point trace and the strong reflection point trace satisfies the energy threshold condition, determine the point trace state of at least one candidate point trace.

[0044] S208, when at least one candidate point is in motion, determine the false detection point from at least one candidate point.

[0045] In S202 of the above embodiment, the target radar system can be a radar system configured with a specific Doppler multiple access (DDMA) waveform. The system includes K transmitting antennas and L receiving antennas. Through radar signal processing, such as coherent processing and incoherent processing, target information is extracted from the echo signal to form a series of dot traces. Each dot trace contains the target's range index value, Doppler index value, and echo energy, as well as the target's state (such as stationary or moving).

[0046] As an optional implementation, a DDMAMIMO radar system includes K transmitting antennas and L receiving antennas, with the phase offset steps for the K transmitting antennas being [PS_1, PS_2, ..., PS_K]. A radial range-radial relative velocity heatmap is obtained by performing coherent and incoherent processing on the received radar signal. M detection points are obtained using an adaptive threshold detection algorithm or its variations. After DDMA demodulation of the M detection points, N target points are obtained; that is, the aforementioned set of points includes N of the aforementioned point objects.

[0047] In step S204 above, the strong reflection point can be a point with echo energy exceeding a preset threshold (P_set), or it can be determined as a strong reflection point if the echo energy of the point at the same position in multiple consecutive frames remains stable and high in multiple frames. No specific restrictions are placed on the determination of strong reflection point here.

[0048] When there is a deviation between the actual phase value configured by the phase shifter and the theoretically designed phase value, the echo energy of the detected point trace may "leak" to other specific frequencies in the Doppler dimension. This phenomenon is more pronounced if strong reflection points exist in the scene, causing points at the "leaking" energy locations to pass the detection threshold and result in false detections. Therefore, this characteristic can be used to determine the correctness of candidate points. Specifically, if a strong reflection point exists in the scene, and the point is located close to the strong reflection point and its Doppler frequency satisfies a specific mathematical relationship (e.g., the frequency difference is an integer multiple of a preset frequency offset), the candidate point may be caused by a phase shifter deviation.

[0049] In DDMAMIMO radar systems, the frequency offset of the waveforms configured for each transmitting antenna ensures orthogonality between the transmitted waveforms. Phase deviations (such as phase shifter phase deviations) can cause additional echo energy to appear at specific Doppler frequency positions relative to the real target. Even if there are no actual moving targets at these positions, the system may incorrectly identify them as moving points.

[0050] It is understandable that the echo energy value is the amplitude value corresponding to a given radial distance index value and radial relative velocity index value, which will not be elaborated here.

[0051] Through the above steps S206-S208, if the first distance index value of the strong reflection point and the second distance index value of at least one candidate point in the candidate point subset satisfy the index difference condition, and the echo energy difference between at least one candidate point and the strong reflection point satisfies the energy threshold condition, the point state of at least one candidate point is determined; if at least one candidate point is in motion, false detection points are determined from at least one candidate point.

[0052] In other words, by determining whether the radial distance index value of the point is equal to or close to the radial distance index value of the strongly reflective target point (i.e., satisfying the above index difference condition), a small number of points that are close to the strongly reflective point in space are located without having to traverse all detection points. Further, it is checked whether the difference in echo energy between the two exceeds a preset judgment threshold. If the threshold is exceeded, the state information of the candidate point is obtained. If the state information indicates that the candidate point is in motion, it is determined to be a (potential) false detection point. The true false detection point can be further screened from the potential false detection point. The true false detection point can be further screened based on whether the velocity index interval between the potential false detection point and the strongly reflective point satisfies the integer multiple condition.

[0053] Through the above-described embodiments of this application, a set of point tracks is determined based on the echo signal of the target radar system. When the set of point tracks includes strong reflection point tracks, a subset of candidate point tracks associated with the strong reflection point tracks is determined from the set of point tracks. The point track distances between the candidate point tracks in the subset of candidate point tracks and the strong reflection point tracks satisfy the target distance condition, quickly locating areas potentially affected by phase shifter phase deviations, thus avoiding a comprehensive analysis of the entire set of point tracks. Furthermore, when the first distance index value of the strong reflection point track and the second distance index value of at least one candidate point track in the subset of candidate point tracks satisfy the index difference condition, and the echo energy difference between at least one candidate point track and the strong reflection point track satisfies the energy threshold condition, the point track state of at least one candidate point track is determined. This achieves the determination of false detection point tracks from at least one candidate point track even when at least one candidate point track is in motion, thereby solving the technical problem of low efficiency in determining false detection point tracks in related technologies.

[0054] In one optional implementation, determining the trace state of at least one candidate trace when the first distance index value of the strong reflection trace and the second distance index value of at least one candidate trace in the subset of candidate traces satisfy the index difference condition, and the echo energy difference between at least one candidate trace and the strong reflection trace satisfies the energy threshold condition, includes:

[0055] S1, determine the difference between the first distance index value of the strong reflection point and the second distance index value of at least one candidate point, and obtain the distance index difference;

[0056] S2, if the absolute value of the distance index difference is less than the first difference threshold, determine the difference between the echo energy value of the strong reflection point and the echo energy value of the candidate point, and obtain the echo energy difference.

[0057] S3, if the echo energy difference is greater than the first energy threshold, determine the status of the candidate point trace.

[0058] As an optional implementation, in step S1 above, by calculating the distance index difference between the strong reflective point and the candidate point, candidate points that are spatially close to the strong reflective point are identified. This is because false positives often appear in the vicinity of the strong reflective point, especially at similar or equal radial distances. Performing subsequent analysis only on candidate points that are radially close to the strong reflective point significantly reduces the amount of data that needs to be processed, thereby reducing computational resource consumption and improving processing speed. The aforementioned distance index difference can be determined based on historical experimental data.

[0059] Further in step S2 above, for candidate traces identified as having a distance index difference from the strong reflection trace less than a first difference threshold, the difference between their echo energy values ​​and the echo energy values ​​of the strong reflection trace is further calculated to obtain the echo energy difference. This identifies traces with significantly lower energy than the strong reflection trace. The aforementioned first difference threshold can be set according to the system's performance requirements.

[0060] Since false detection points caused by phase shifter phase deviation will have different Doppler frequencies, i.e. different radial relative velocity values, in step S3 above, by checking the state of candidate points, the algorithm can further filter out potential false detection points and false detection points.

[0061] The embodiments described in this application integrate distance relationships, energy difference analysis, and dot state checks to determine whether a dot is a false positive. This improves the accuracy of identifying potential false positives and reduces the likelihood of false positives.

[0062] In an optional implementation, determining false detection points from at least one candidate point while at least one candidate point is in motion further includes:

[0063] S1, obtain the first velocity index value of the strong reflection point and the second velocity index value of the current candidate point, and calculate the velocity index difference between the first velocity index value and the second velocity index value;

[0064] S2, if the velocity index difference meets the target interval condition, the current candidate point is determined as a false detection point. The target interval condition is determined according to the waveform parameters of the target radar system.

[0065] Since the frequency offset of the waveforms of each transmitting antenna in the DDMA MIMO radar system is set based on a fixed phase step, and the phase deviation of the phase shifter is fixed with the fixed step size, it exhibits a periodic spurious phenomenon in the Doppler spectrum. Therefore, when the index value interval between the current candidate point trace and the identified strong reflection point trace in the radial relative velocity exactly matches the periodic integer multiple relationship corresponding to the phase deviation of the phase shifter, the current candidate point trace can be further determined to be the false detection point trace.

[0066] The process of determining false detection points described above will be explained below using a complete implementation method:

[0067] Obtaining the detected point trace: For example, a DDMA MIMO radar system includes K=3 transmitting antennas and L=1 receiving antenna, with the corresponding phase offset steps for the K=3 transmitting antennas being [PS_1,PS_2,PS_3]=[0,0.25pi,0.75pi]. A radial range-radial relative velocity heatmap is obtained by performing coherent and incoherent processing on the radar received signal, such as... Figure 3 The diagram shows the radial distance index value - radial relative velocity index value. M detection points are obtained through an adaptive threshold detection algorithm or its variations. For the m-th detection point, the relevant information includes the distance index value, Doppler index value, and target point amplitude, denoted as R_m, D_m, and P_m, respectively. The point list contains relevant information for M = 9 detection points:

[0068] The m=1th detected point (R_1=9, D_1=0, P_1=147dB);

[0069] The m=2nd detected point (R_2=9, D_2=64, P_2=149dB);

[0070] The m=3rd detected point (R_3=9, D_3=128, P_3=114dB);

[0071] The m=4th detected point (R_4=9, D_4=192, P_4=148dB);

[0072] The m=5th detected point (R_5=9, D_5=320, P_5=111dB);

[0073] The m=6th detected point (R_6=9, D_6=448, P_6=115dB);

[0074] The m=7th detected point (R_6=17, D_6=0, P_6=130dB);

[0075] The m=8th detected point (R_6=17, D_6=64, P_6=130dB);

[0076] The m=9th detected point (R_6=17, D_6=192, P_6=130dB);

[0077] Obtaining target point information: For example, for the above 9 detected points, after DDMA demodulation, N=4 target points are obtained (i.e., the first set of points mentioned above). Taking a radial distance index value of 9 as an example, such as... Figure 4There are 3 marked points corresponding to the target traces after DDMA demodulation. For the nth trace, the trace-related information includes the radial distance index value, the radial relative velocity index value, the trace amplitude, and the trace state, which are denoted as RT_n, DT_n, PT_n, and ST_n respectively. The list of target trace-related information is as follows (hereinafter, to avoid confusion with the final output target traces and for the convenience of expression, the "target trace" is directly abbreviated as "trace"):

[0078] The n = 1st trace (RT_1 = 9, DT_1 = 0, PT_1 = 147 dB, ST_1 = stationary), corresponding to m = 1;

[0079] The n = 2nd trace (RT_2 = 9, DT_2 = 128, PT_2 = 114 dB, ST_2 = moving), corresponding to m = 3;

[0080] The n = 3rd trace (RT_3 = 9, DT_3 = 448, PT_3 = 115 dB, ST_3 = moving), corresponding to m = 6;

[0081] The n = 4th trace (RT_4 = 17, DT_4 = 0, PT_4 = 130 dB, ST_4 = stationary), corresponding to m = 8;

[0082] Recognition of strong reflection target traces: For example, set the strong reflection trace threshold P_set = 140 dB. The radial distance index value threshold R_set = the number of fast-time samples = 256.

[0083] The n = 1st trace satisfies PT_1 > P_set and RT_1 < R_set, and it is determined that the 1st trace is a strong reflection trace.

[0084] The n = 2nd trace satisfies the condition RT_2 < R_set but does not satisfy the condition PT_2 > P_set, and it is determined that the 2nd trace is a non-strong reflection trace.

[0085] The n = 3rd trace satisfies the condition RT_3 < R_set but does not satisfy the condition PT_3 > P_set, and it is determined that the 3rd trace is a non-strong reflection trace.

[0086] The n = 4th trace satisfies the condition RT4 < R_set but does not satisfy the condition PT_4 > P_set, and it is determined that the 4th trace is a non-strong reflection trace.

[0087] Furthermore, the judgment of misdetected target traces includes: determining candidate traces, obtaining potential misdetected traces, and judging whether the potential misdetected traces are misdetected traces.

[0088] Specifically, the candidate traces are determined as follows: The number of traces to be extracted is set to i = 3. In this example, the total number of traces is N = 4, and the strongly reflective trace is the n = 1st trace (it should be noted that in actual operation, a large number of traces will be generated, so the number of traces to be extracted needs to be set to only obtain a small number of traces for judgment. In this example, the number of traces is small, so we take the extraction of all traces near the strongly reflective point as an example). Therefore, the subset of candidate traces is:

[0089] The n=1+1=2th point (RT_2=9, DT_2=128, PT_2=114dB, ST_2=motion) corresponds to m=3;

[0090] The n=1+2=3rd point (RT_3=9, DT_3=448, PT_3=115dB, ST_3=motion) corresponds to m=6;

[0091] The n=1+3=4th dot (RT_4=17, DT_4=0, PT_4=130dB, ST_4=stationary) corresponds to m=8;

[0092] Obtain potential false positives: for example, set the decision threshold to 25dB.

[0093] Among the candidate points mentioned above, only the radial distance index values ​​corresponding to the n=2nd and n=3rd points are equal to the radial distance index values ​​of the strong reflection points. Furthermore, the difference between the echo energy of the strong reflection points and the echo energy of the candidate points is greater than the judgment threshold. Additionally, the candidate points are in motion. Therefore, they are determined to be potential false positives. The list of potential false positives is as follows:

[0094] The first potential false positive target point is the n=2nd target point (RT_2=9, DT_2=128, PT_2=114dB, ST_2=motion), corresponding to m=3.

[0095] The second potential false positive target point is the n=3rd target point (RT_3=9, DT_3=448, PT_3=115dB, ST_3=motion), corresponding to m=6.

[0096] Determine whether a potential false detection point is a false detection point: for example, interval δ = 64.

[0097] The first potential false detection point satisfies the judgment condition that the interval between the radial relative velocity index value of the point and the strong reflection point is an integer multiple of δ = 64. Therefore, the point is determined to be a false detection point and is deleted.

[0098] The second potential false positive mark satisfies the condition that the interval between its radial relative velocity index value and that of the strong reflection mark is a multiple of δ = 64. Therefore, this mark is determined to be a false positive mark and is deleted. False positive marks are as follows: Figure 5The markings corresponding to the falsely detected target points are shown in the figure.

[0099] The final output dots are as follows Figure 6 The final output shows the marker corresponding to the target point, which is then used for subsequent signal processing.

[0100] In one optional implementation, if the velocity index difference meets the target interval condition, the current candidate point is identified as a false detection point, including:

[0101] If the velocity index difference between the first velocity index value and the second velocity index value satisfies the condition that the phase offset difference in the waveform parameters of the target radar system is an integer multiple, the current candidate point is determined to be a false detection point.

[0102] Because there is a fixed phase deviation between the actual frequency offset of the phase shifter and the theoretical design value, the relative position of the echo energy of the strong reflection point that "leaks" to the relevant Doppler index value is fixed. Therefore, the interval between the false detection point and the strong reflection point satisfies the relationship of an integer multiple determined by the phase difference and the code design.

[0103] In other words, if the radial relative velocity index difference between the strong reflection point and the current candidate point satisfies the aforementioned integer multiple condition for waveform design and phase difference matching, it indicates that the appearance of the candidate point is due to energy leakage from the strong reflection point, rather than a true target echo signal. In this case, the system will determine that the current candidate point is a false detection point and remove it.

[0104] The embodiments described in this application utilize the inherent regularity of the effect of phase shifter phase deviation on signal characteristics. Specifically, the Doppler spectrum of the radar signal changes when phase deviation exists, and this can be determined by detecting whether the interval between the radar signal and the strong reflective target is an integer multiple of the target's distance. This enables rapid localization of potential false detection points, avoids redundant traversal and complex calculations of all points, reduces the computational complexity and time consumption of signal processing, and improves the overall efficiency and performance of the system.

[0105] In an alternative implementation, when the dot set includes strongly reflective dots, determining a subset of candidate dots associated with the strongly reflective dots from the dot set further includes:

[0106] S1, determine the sequence number of the strong reflection point in the point information list, wherein the point information list is obtained by sorting the point objects in the point set according to the radial distance index value distribution;

[0107] S2, if the sequence number interval between at least one reference point and a strongly reflective point in the point information list is less than or equal to the sequence number interval threshold, at least one reference point is determined as a candidate point.

[0108] Describe steps S1 - S2 in a complete implementation manner. Assume that after DDMA demodulation, the above - mentioned list of track information is obtained according to the distribution of radial - distance index values:

[0109] The 1st track (RT_1 = 9, DT_1 = 0, PT_1 = 147 dB, ST_1 = stationary);

[0110] The 2nd track (RT_2 = 9, DT_2 = 128, PT_2 = 114 dB, ST_2 = moving)…

[0111] The nth track (RT_3 = 9, DT_3 = 448, PT_= 115 dB, ST_3 = moving)…

[0112] The xth track (RT_4 = 17, DT_4 = 0, PT_4 = 130 dB, ST_ = stationary);

[0113] Among them, the nth track is determined as a strong - reflection track. Taking n as the center, the relevant information of the i tracks before and after it (i.e., the above - mentioned candidate tracks) can be extracted, that is, including the relevant information of the tracks numbered n - i, …, n - 1, n + 1, …, n + i. Furthermore, the sequence - number interval between the sequence number of the obtained candidate track and the sequence number n of the strong - reflection track is less than or equal to i.

[0114] [[ID=,19]]Through the above - mentioned implementation manner recorded in this application, without traversing the entire track set again, based on the selected strong - reflection track, further judgment can be made on the candidate tracks that meet the sequence - number interval condition, improving the processing efficiency. <,

[0115] In an optional implementation manner, when the track set includes strong - reflection tracks, before determining the subset of candidate tracks associated with the strong - reflection tracks from the track set, it further includes:

[0116] S1, obtain the echo - energy value of the track object in the track set;

[0117] S2, obtain the distance - index value of the track object when the echo - energy value is greater than the second energy threshold;

[0118] S3, determine the track object as a strong - reflection track when the distance - index value is less than the target sample - acquisition value.

[0119] As an optional implementation manner, set the strong - reflection target - track threshold, that is, the above - mentioned second energy threshold is P_set, and the above - mentioned target sample - acquisition value can be the number of fast - time samplings = the radial - distance index - value threshold R_set. If for the nth detected target track P_n > P_set and R_n < R_set, then determine the nth detected target track as a strong - reflection target track.

[0120] It should be noted that the strong reflection target trace threshold P_set and the radial distance index value threshold R_set can be set according to system requirements. Each threshold parameter can be set as a single threshold (i.e., as described above) or multiple thresholds. For example, the system can set a relatively high P_set threshold within a distance of 0 to 100 unit distances, representing a threshold for high energy at close range to reduce false detection of strong reflection traces at close range; and set a relatively low P_set threshold within a distance range of 101 to 256 unit distances, representing a threshold for low energy at far range to improve the detection rate of strong reflection traces at far range. This application does not limit this.

[0121] The following uses a complete implementation manner to fully describe this application, such as the process Figure 7 as shown:

[0122] S702. Obtain the detected traces: The DDMA MIMO radar system includes K transmitting antennas and L receiving antennas. The phase offset steps corresponding to the K transmitting antennas are [PS_1, PS_2,..., PS_K]. Through coherent and non-coherent processing of the radar received signal, a radial distance - radial relative velocity heat map is obtained. Through an adaptive threshold detection algorithm or its variant, M detected traces are obtained.

[0123] S704. Obtain trace-related information: For the M detected traces, after completing DDMA demodulation, N target traces (i.e., the trace objects in the first trace set) are obtained. For the nth target trace, the target trace-related information includes the radial distance index value, the radial relative velocity index value, the target trace amplitude, and the target state, which are respectively denoted as RT_n, DT_n, PT_n, and ST_n.

[0124] S706. Identify strong reflection target traces: Set the strong reflection target trace threshold P_set and the radial distance index value threshold R_set. If for the nth detected target trace P_n > P_set and R_n < R_set, then it is determined that the nth detected target trace is a strong reflection target trace. It should be noted that the strong reflection target trace threshold P_set and the radial distance index value threshold R_set can be set according to system requirements. Each threshold parameter can be set as a single threshold (i.e., as described above) or multiple thresholds. This application does not limit this.

[0125] S708. Judge and suppress false detected target traces. The specific process is as shown in the process Figure 8 as shown:

[0126] S802, Determine candidate target traces: If the nth target trace is determined to be a strong reflective target trace, then extract the relevant information of the i target traces before and after n from the target trace relevant information list (i.e., the above-mentioned candidate trace subset), which includes the relevant information of ni, ..., n-1, n+1, ..., n+i traces. It should be noted that the selection of i can be set based on the system design. The selected traces are denoted as candidate traces.

[0127] S804, obtain potential false detection target traces: traverse the 2i candidate traces in the previous step. If the radial distance index value corresponding to a certain target trace is equal to or close to the radial distance index value of a strong reflection target trace, and the difference between the echo energy of the strong reflection target trace and the echo energy corresponding to the candidate trace is greater than the judgment threshold, and the candidate trace is in motion, then the candidate trace is determined to be a potential false detection target trace.

[0128] S806, determine whether the potential false detection target mark is a false detection target mark: if the interval between the radial relative velocity index value of the potential false detection target mark and the radial relative velocity index value of the strong reflection target mark satisfies the relationship of an integer multiple of δ, determine that the potential false detection target mark is a false detection target mark caused by the phase shifter phase deviation, and delete the target mark information.

[0129] The S710 is used for subsequent signal processing.

[0130] It operates on the target point traces in the DDMA demodulation output, rather than the detected point traces, thus enabling confirmation only for potential false detection targets. It eliminates the need to traverse all target point traces that meet the specified radial distance condition and perform a cumulative summation calculation for each target point trace, thereby reducing computational resources and time consumption.

[0131] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0132] According to another aspect of the embodiments of this application, a device for determining false detection points for implementing the above-described method for determining false detection points is also provided. For example... Figure 9 As shown, the device includes:

[0133] The first determining unit 902 determines a set of points based on the echo signal from the target radar system, wherein the set of points includes multiple point objects;

[0134] The second determining unit 904, when the set of points includes strongly reflective points, determines a subset of candidate points associated with the strongly reflective points from the set of points, wherein the point distance between the candidate points in the subset of candidate points and the strongly reflective points satisfies the target distance condition.

[0135] The third determining unit 906 determines the state of at least one candidate point when the first distance index value of the strong reflection point and the second distance index value of at least one candidate point in the candidate point subset satisfy the index difference condition, and the echo energy difference between at least one candidate point and the strong reflection point satisfies the energy threshold condition.

[0136] The fourth determining unit 908 determines the false detection point from at least one candidate point when at least one candidate point is in motion.

[0137] Optionally, the third determining unit 906 further includes: a state determining module, used to determine the difference between the first distance index value of the strong reflection point and the second distance index value of at least one candidate point, to obtain a distance index difference; if the absolute value of the distance index difference is less than the first difference threshold, to determine the difference between the echo energy value of the strong reflection point and the echo energy value of the candidate point, to obtain an echo energy difference; if the echo energy difference is greater than the first energy threshold, to determine the point state of the candidate point.

[0138] Optionally, the aforementioned state determination module includes: a first acquisition module, used to acquire a first velocity index value of a strong reflection point and a second velocity index value of a current candidate point, and calculate the velocity index difference between the first velocity index value and the second velocity index value; if the velocity index difference satisfies the target interval condition, the current candidate point is determined as a false detection point, wherein the target interval condition is determined according to the waveform parameters of the target radar system.

[0139] Optionally, the first acquisition module is further configured to determine the current candidate point as a false detection point if the velocity index difference between the first velocity index value and the second velocity index value satisfies the condition that the phase offset difference in the waveform parameters of the target radar system is an integer multiple.

[0140] Optionally, the second determining unit 904 is further configured to determine the serial number of the strong reflection point in the point information list, wherein the point information list is obtained by sorting the point objects in the point set according to the radial distance index value distribution; if the serial number interval between at least one reference point and the strong reflection point in the point information list is less than or equal to the serial number interval threshold, at least one reference point is determined as a candidate point.

[0141] Optionally, the second determining unit 904 further includes a second acquisition module, used to acquire the echo energy value of the trace object in the trace set; acquire the distance index value of the trace object when the echo energy value is greater than the second energy threshold; and determine the trace object as a strong reflective trace when the distance index value is less than the target sample acquisition value.

[0142] For specific implementation examples, please refer to the examples shown in the above method for determining false detection points; these will not be repeated here.

[0143] The memory 1002 can be used to store software programs and modules, such as the program instructions / modules corresponding to the method and apparatus for determining false detection points in this embodiment of the invention. The processor 1004 executes various functional applications and data processing by running the software programs and modules stored in the memory 1002, thereby realizing the aforementioned method for determining false detection points. The memory 1002 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 1002 may further include memory remotely located relative to the processor 1004, and these remote memories can be connected to the terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof. Specifically, the memory 1002 may be used, but is not limited to, for storing file information such as target files. As an example, such as Figure 10 As shown, the memory 1002 may include, but is not limited to, the first determining unit 902, the second determining unit 904, the third determining unit 906, and the fourth determining unit 908 in the aforementioned false detection point determination device. Furthermore, it may include, but is not limited to, other module units in the aforementioned false detection point determination device, which will not be elaborated upon in this example.

[0144] Optionally, the transmission device 1006 described above is used to receive or send data via a network. Specific examples of the network described above may include wired networks and wireless networks. In one example, the transmission device 1006 includes a Network Interface Controller (NIC), which can be connected to other network devices and routers via a network cable to communicate with the Internet or a local area network. In another example, the transmission device 1006 is a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0145] In addition, the above-mentioned electronic device also includes a display 1008 and a connection bus 1010 for connecting the various module components in the above-mentioned electronic device.

[0146] According to one aspect of this application, a computer program product is provided, comprising a computer program / instructions containing program code for performing the methods shown in the flowchart. In such embodiments, the computer program can be downloaded and installed from a network via a communication component, and / or installed from a removable medium. When the computer program is executed by a central processing unit, it performs various functions provided in embodiments of this application.

[0147] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0148] It should be noted that the computer system of the electronic device is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0149] Specifically, according to embodiments of this application, the processes described in the various method flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication component, and / or installed from a removable medium. When the computer program is executed by a central processing unit, it performs various functions defined in the system of this application.

[0150] According to one aspect of this application, a computer-readable storage medium is provided, wherein a processor of a computer device reads computer instructions from the computer-readable storage medium, and executes the computer instructions, causing the computer device to perform the methods provided in the various alternative implementations described above.

[0151] Optionally, in this embodiment, the computer-readable storage medium described above may be configured to store a computer program for performing the following steps:

[0152] S1, determine the set of points based on the echo signal of the target radar system, wherein the set of points includes multiple point objects;

[0153] S2, if the set of points includes strongly reflective points, determine a subset of candidate points associated with the strongly reflective points from the set of points, wherein the point distance between the candidate points in the subset of candidate points and the strongly reflective points satisfies the target distance condition.

[0154] S3, if the first distance index value of the strong reflection point trace and the second distance index value of at least one candidate point trace in the candidate point trace subset satisfy the index difference condition, and the echo energy difference between at least one candidate point trace and the strong reflection point trace satisfies the energy threshold condition, determine the point trace state of at least one candidate point trace.

[0155] S4, when at least one candidate point is in motion, determine the false detection point from at least one candidate point.

[0156] Optionally, in this embodiment, those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware of an electronic device. The program can be stored in a computer-readable storage medium, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0157] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0158] If the integrated units in the above embodiments are implemented as software functional units and sold or used as independent products, they can be stored in the aforementioned computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part 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 to cause one or more computer devices (which may be personal computers, servers, or network devices, etc.) to execute all or part of the steps of the methods of the various embodiments of this application.

[0159] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0160] In the several embodiments provided in this application, it should be understood that the disclosed user equipment can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection of units or modules may be electrical or other forms.

[0161] The units described as separate components may or may not be physically separate. The 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 the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0162] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0163] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for determining false detection points, characterized in that, include: A set of points is determined based on the echo signal from the target radar system, wherein the set of points includes multiple point objects; When the set of dots includes strongly reflective dots, determining a subset of candidate dots associated with the strongly reflective dots from the set of dots includes: determining the index of the strongly reflective dots in a dot information list, wherein the dot information list is obtained by sorting the dot objects in the dot set according to the radial distance index value distribution; if the index interval between at least one reference dot in the dot information list and the strongly reflective dots is less than or equal to an index interval threshold, determining at least one reference dot as a candidate dot, wherein the dot distance between the candidate dot in the subset of candidate dot and the strongly reflective dots satisfies the target distance condition; If the first distance index value of the strong reflection point trace and the second distance index value of at least one candidate point trace in the subset of candidate point traces satisfy the index difference condition, and the echo energy difference between at least one candidate point trace and the strong reflection point trace satisfies the energy threshold condition, the point trace state of at least one candidate point trace is determined. When at least one of the candidate points is in motion, a false detection point is determined from at least one of the candidate points.

2. The method according to claim 1, characterized in that, The determination of the trace state of at least one candidate trace when the first distance index value of the strongly reflecting trace and the second distance index value of at least one candidate trace in the subset of candidate traces satisfy the index difference condition, and the echo energy difference between at least one candidate trace and the strongly reflecting trace satisfies the energy threshold condition, includes: The difference between the first distance index value of the strongly reflective point and the second distance index value of at least one of the candidate points is determined to obtain the distance index difference; If the absolute value of the distance index difference is less than the first difference threshold, the difference between the echo energy value of the strong reflection point and the echo energy value of the candidate point is determined to obtain the echo energy difference. If the echo energy difference is greater than a first energy threshold, the state of the candidate point is determined.

3. The method according to claim 2, characterized in that, The step of determining false detection points from at least one candidate point when at least one of the candidate point traces is in motion further includes: Obtain the first velocity index value of the strong reflection point and the second velocity index value of the current candidate point, and calculate the velocity index difference between the first velocity index value and the second velocity index value; If the velocity index difference satisfies the target interval condition, the current candidate point is determined as a false detection point, wherein the target interval condition is determined based on the waveform parameters of the target radar system.

4. The method according to claim 3, characterized in that, The step of determining the current candidate point as a false detection point when the velocity index difference meets the target interval condition includes: If the velocity index difference between the first velocity index value and the second velocity index value satisfies the condition that the phase offset difference in the waveform parameters of the target radar system is an integer multiple, then the current candidate point is determined to be the false detection point.

5. The method according to claim 1, characterized in that, If the set of dots includes strongly reflective dots, before determining the subset of candidate dots associated with the strongly reflective dots from the set of dots, the method further includes: Obtain the echo energy value of the trace object in the trace set; If the echo energy value is greater than the second energy threshold, obtain the distance index value of the trace object; If the distance index value is less than the target sample collection value, the point object is determined to be the strong reflective point.

6. A device for determining false detection points, characterized in that, include: The first determining unit determines a set of point traces based on the echo signal from the target radar system, wherein the set of point traces includes multiple point trace objects; The second determining unit, when the set of traces includes strongly reflective traces, determines a subset of candidate traces associated with the strongly reflective traces from the set of traces, including: determining the sequence number of the strongly reflective trace in a trace information list, wherein the trace information list is obtained by sorting the trace objects in the set of traces according to the radial distance index value distribution; and determining at least one of the reference traces as candidate traces when the sequence number interval between at least one reference trace in the trace information list and the strongly reflective trace is less than or equal to a sequence number interval threshold, wherein the trace distance between the candidate traces in the subset of candidate traces and the strongly reflective trace satisfies the target distance condition. The third determining unit determines the trace state of at least one of the candidate traces when the first distance index value of the strong reflection trace and the second distance index value of at least one candidate trace in the subset of candidate traces satisfy the index difference condition, and the echo energy difference between at least one of the candidate traces and the strong reflection trace satisfies the energy threshold condition. The fourth determining unit determines false detection points from at least one of the candidate points when at least one of the candidate points is in motion.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein the program is executed by an electronic device to perform the method according to any one of claims 1 to 5.

8. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to execute the method described in any one of claims 1 to 5 through the computer program.

9. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method described in any one of claims 1 to 5.

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