Radar-based range detection methods and radar detection devices

Abstract

This application relates to the field of radar detection technology, and provides a radar-based range detection method and radar detection device, including: determining the signal-to-noise ratio (SNR) of multiple received scattered signals; determining a current target signal from the multiple scattered signals based on the SNR of the multiple scattered signals, the SNR of multiple historical target signals, and the distances of multiple historical targets; and determining the current target distance based on the current target signal, where the current target distance is the distance between the current target object and the radar. According to the method provided in this application, by expanding the range gate and determining the target signal jointly based on historical target signals and multiple scattered signals, the amount of data available for judging the target signal can be increased, thereby improving the detection probability. Furthermore, because the computational load of the method used in this application in determining the current target signal is much less than that of algorithms such as track initiation, the method of this application can achieve real-time target tracking while improving the detection probability.

Description

Technical Field

[0001] This application belongs to the field of radar detection technology, and in particular relates to a radar-based distance detection method and radar detection device. Background Technology

[0002] In current radar distance detection methods, due to limited radar computing resources, if the radar needs to process too much data in a short period, it will truncate some of the acquired data for processing. This results in data loss, reducing the amount of usable data for determining the target signal and lowering the target detection probability. While methods like track initiation and track tracking can be used to improve the target detection probability, their computational complexity increases radar processing time. This leads to a significant delay between the radar's calculated target distance and the actual target distance, preventing real-time target tracking. Summary of the Invention

[0003] This application provides a radar-based distance detection method and radar detection device, which can solve the problems of low target detection probability and large delay when existing radars are tracking targets.

[0004] In a first aspect, embodiments of this application provide a radar-based distance detection method, including:

[0005] Determine the signal-to-noise ratio of the received multiple scattered signals, wherein the multiple scattered signals are detection signals of the radar scattered by multiple objects;

[0006] Based on the signal-to-noise ratio of the plurality of scattered signals, the signal-to-noise ratio of the plurality of historical target signals, and the distances of the plurality of historical targets, a current target signal is determined from the plurality of scattered signals. The target signal is the radar detection signal scattered by the target object. The plurality of historical target signals are the detection signals scattered by the target object before reaching the current position. The plurality of historical target distances are the distances between the target object and the radar before reaching the current position.

[0007] The current target distance is determined based on the current target signal, where the current target distance is the distance between the target object and the radar.

[0008] In one possible implementation of the first aspect, at least one first signal among multiple scattered signals can be determined. Then, based on the signal-to-noise ratio of the multiple scattered signals, the signal-to-noise ratio of multiple historical target signals, and the distances of multiple historical targets, it is determined whether the first signal conforms to the energy increase law and the motion trend of the radar relative to the target object; the first signal that conforms to the energy increase law and the motion trend of the radar relative to the target object is determined as the target signal.

[0009] For example, the signal-to-noise ratio of the first signal is greater than a first preset threshold.

[0010] For example, the energy increase law is that the signal-to-noise ratio of the target signal is negatively correlated with the target distance corresponding to the target signal.

[0011] In one possible implementation of the first aspect, at least one first signal and historical target signals can be arranged in descending order of target distance to obtain a first sequence. Then, by judging whether the signal-to-noise ratio of the first signal in the first sequence conforms to an increasing trend, it can be determined whether the first signal conforms to the law of increasing energy. By judging whether the distance-time relationship of the first signal in the first sequence conforms to the speed and direction of the radar relative to the target object, it can be determined whether the first signal conforms to the motion trend of the radar relative to the target object.

[0012] In one possible implementation of the first aspect, a time-range-signal-noise ratio curve of the historical target signals within a preset time period can be plotted based on the signal-to-noise ratios of multiple historical target signals and the distances to multiple historical targets. Then, based on the time-range-signal-noise ratio curve, it can be determined whether the first signal conforms to the energy increase law and the motion trend of the radar relative to the target object.

[0013] According to the method provided in this application, by expanding the range gate and determining the target signal based on historical target signals and multiple scattered signals, the amount of data available for judging the target signal can be increased, thereby improving the detection probability. Furthermore, because the computational load of the method used in this application in determining the current target signal is much less than that of algorithms such as track initiation, the method of this application can achieve real-time target tracking while improving the detection probability.

[0014] Secondly, embodiments of this application provide a radar detection device, including: a processing unit;

[0015] The processing unit is used for:

[0016] Determine the signal-to-noise ratio of the received multiple scattered signals, wherein the multiple scattered signals are detection signals of the radar scattered by multiple objects;

[0017] Based on the signal-to-noise ratio of the plurality of scattered signals, the signal-to-noise ratio of the plurality of historical target signals, and the distances of the plurality of historical targets, a current target signal is determined from the plurality of scattered signals. The target signal is the radar detection signal scattered by the target object. The plurality of historical target signals are the detection signals scattered by the target object before reaching the current position. The plurality of historical target distances are the distances between the target object and the radar before reaching the current position.

[0018] The current target distance is determined based on the current target signal, where the current target distance is the distance between the target object and the radar.

[0019] In one possible implementation of the second aspect, the processing unit 710 may specifically be used to: determine at least one first signal among a plurality of scattered signals; determine whether the first signal conforms to the energy increase law and the motion trend of the radar relative to the target object based on the signal-to-noise ratio of the plurality of scattered signals, the signal-to-noise ratio of the plurality of historical target signals and the distance of the plurality of historical targets; and determine the first signal that conforms to the energy increase law and the motion trend of the radar relative to the target object as the current target signal.

[0020] For example, the signal-to-noise ratio of the first signal is greater than a first preset threshold.

[0021] For example, the energy increase law is that the signal-to-noise ratio of the target signal is negatively correlated with the target distance corresponding to the target signal.

[0022] In one possible implementation of the second aspect, the processing unit 710 may specifically be used to: arrange at least one first signal and historical target signals in descending order of target distance to obtain a first sequence; determine whether the first signal conforms to the energy increase law by judging whether the signal-to-noise ratio of the first signal in the first sequence conforms to the increasing trend; and determine whether the first signal conforms to the motion trend of the radar relative to the target object by judging whether the distance-time relationship of the first signal in the first sequence conforms to the speed and direction of the radar relative to the target object.

[0023] In one possible implementation of the second aspect, the processing unit 710 may be used to: plot the time-range-signal-noise ratio curve of the historical target signal within a preset time period based on the signal-to-noise ratio of multiple historical target signals and the distance of multiple historical targets; and determine whether the first signal conforms to the energy increase law and the motion trend of the radar relative to the target object based on the time-range-signal-noise ratio curve.

[0024] Thirdly, embodiments of this application provide a radar detection device, including: a memory and a processor, wherein the processor can be used to execute a program (instructions) stored in the memory to implement the method provided in the first aspect above.

[0025] Fourthly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, which, when executed, can implement the method provided in the first aspect above.

[0026] Fifthly, embodiments of this application provide a computer program product that, when run on a terminal device, causes the terminal device to execute any of the methods described in the first aspect.

[0027] It is understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here.

[0028] The beneficial effects of this application's embodiments compared to the prior art are as follows: According to the method provided in this application, by expanding the range gate and jointly determining the target signal based on historical target signals and multiple scattering signals, the amount of data available for judging the target signal can be increased, thereby improving the detection probability. Furthermore, because the computational load of the method used in this application in determining the current target signal is far less than that of algorithms such as track initiation, the method of this application can achieve real-time target tracking while improving the detection probability. Attached Figure Description

[0029] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0030] Figure 1 This is a flowchart illustrating a distance detection method;

[0031] Figure 2 This is a schematic diagram illustrating the relationship between detection probability and a first preset threshold under different false alarm probabilities, provided in an embodiment of this application.

[0032] Figure 3 This is a schematic diagram illustrating the distance-time relationship provided in one embodiment of this application;

[0033] Figure 4 This is a schematic diagram illustrating the distance-time-signal-noise ratio relationship provided in an embodiment of this application;

[0034] Figure 5 This is a schematic diagram of the detection probability-first preset threshold provided in an embodiment of this application;

[0035] Figure 6 This is a schematic flowchart of a radar-based distance detection method provided in an embodiment of this application;

[0036] Figure 7 This is a schematic diagram illustrating the distance-time-signal-noise ratio relationship provided in another embodiment of this application;

[0037] Figure 8 This is a schematic diagram of the radar detection device provided in the embodiments of this application;

[0038] Figure 9 This is a schematic diagram of the radar detection device provided in the embodiments of this application. Detailed Implementation

[0039] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0040] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0041] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0042] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0043] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0044] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0045] For ease of explanation, the following concepts will be explained before describing the radar-based range detection method provided in this application.

[0046] False alarm probability: The false alarm probability of radar detection is the probability of detecting a target when only noise exists in the radar signal.

[0047] In one range detection method, the presence of a target is determined by comparing the signal-to-noise ratio (SNR) of multiple scattered signals with a first preset threshold. Specifically, if the SNR of multiple scattered signals is greater than or equal to the first preset threshold, then the scattered signal is considered a target signal. Therefore, the false alarm probability can also be interpreted as the probability that the SNR of multiple scattered signals is greater than or equal to the first preset threshold when only noise is present.

[0048] For example, multiple scattered signals are radar detection signals scattered by multiple objects. The radar detection signal is the electromagnetic wave emitted by the radar.

[0049] For example, the false alarm probability of radar detection in the prior art can be obtained by the following formula:

[0050]

[0051] Among them, P fa Let ψ be the false alarm probability. 2 V represents the noise variance. T This is the first preset threshold.

[0052] Accordingly, the first preset threshold used in radar detection in the prior art can be calculated using the following formula:

[0053]

[0054] Detection probability: The detection probability is the probability that the target signal will appear if both the target signal and noise are present in the detection signal. That is, the probability that the signal-to-noise ratio of the detection signal is greater than or equal to a first preset threshold if both the target signal and noise are present in the detection signal.

[0055] For example, the detection probability of radar detection in the prior art can be obtained by the following formula:

[0056]

[0057] Among them, P D For the detection probability, A is the amplitude of the sinusoidal detection wave emitted by the radar, and F is an approximately accurate calculation function.

[0058] Specifically, the standard expression for the F function is as follows:

[0059]

[0060] Figure 1 A flowchart of a distance detection method is shown.

[0061] See Figure 1 Current radar distance detection methods typically involve converting the acquired time-domain signal into a digital signal, followed by denoising processing using software to obtain valid data. This valid data is then processed using methods such as FFT (Fast Fourier Transform) and constant false alarm rate (CFAR) to obtain the signal-to-noise ratio (SNR) of the scattered signal. The target signal is then determined based on the SNR, thus calculating the distance between the target and the radar. When processing a limited number of signals or when sufficient time allows, the SNR of all scattered signals is calculated to identify the target signal.

[0062] However, when MCU (Microcontroller Unit) computing resources are limited, or when the target's movement speed is extremely high and the chirp signal acquired by the radar is short, to ensure computing speed, the computational load must be reduced, processing only the important and effective data. See also Figure 1 The target range detection method shown involves the MCU selecting data from valid data where the range falls within a preset range after a fixed range threshold is established. For example, if the radar determines, based on historical target range data, that the current distance between the target and the radar is within 30 meters, then the radar will only process data from the scattered signals within 30 meters of the multiple scattered signals.

[0063] Then, it is determined whether the signal-to-noise ratio (SNR) of the scattered signal within a preset range is greater than or equal to a first preset threshold. If the SNR of the signal is greater than or equal to the first preset threshold, the signal is identified as the target signal, and the distance corresponding to the signal is determined as the target distance, thus achieving distance detection. However, using this method for distance detection will result in the loss of signals outside the preset range, reducing the amount of usable data and lowering the probability of target detection.

[0064] Based on the above processing methods, in order to improve the target detection probability, post-processing data methods such as track initiation and track tracking are generally used to improve the target detection probability. However, the processing of track initiation and track tracking methods is very complex, which greatly increases the computational load on the MCU and the time required for data processing. This results in a delay in the distance of the detected target relative to a rapidly moving target, making real-time detection and tracking of the target impossible.

[0065] Therefore, traditional detection methods cannot guarantee the detection probability when the target is moving at a very high speed and the chirp signal acquired by the radar is short.

[0066] Figure 2 This illustration shows a schematic diagram of the relationship between detection probability and a first preset threshold under different false alarm probabilities, as demonstrated in an embodiment of this application.

[0067] Specifically, Figure 2 It is drawn based on the formulas for the false alarm probability and the detection probability mentioned above.

[0068] Current distance detection methods can increase the detection probability by decreasing a first preset threshold; however, see... Figure 2 With the first preset threshold unchanged, the higher the detection probability, the higher the false alarm probability. A higher false alarm probability means a lower accuracy in detecting targets.

[0069] Therefore, while ensuring the detection probability, it is also necessary to ensure that the false alarm probability does not increase, that is, to ensure that the accuracy of target detection does not decrease. To ensure that the false alarm probability does not increase, a more accurate method for determining the target signal should be adopted.

[0070] In view of this, this application provides a radar-based range detection method. Compared with current range detection methods, this application expands the range gate range by determining the target signal based on historical target signals and multiple scattered signals, thereby increasing the amount of data available for target signal determination and improving the detection probability. Because the computational load of the method used in this application in determining the current target signal is much less than that of algorithms such as track initiation, it can achieve real-time target tracking while improving the detection probability. Furthermore, by adding a discrimination condition for determining the target signal from multiple scattered signals, the detection probability can be improved without increasing the false alarm probability.

[0071] The radar-based distance detection method provided in this application can be applied to radar or other devices that use radar to perform detection functions, such as drones and vehicles. This application does not impose any restrictions on the specific types of such devices.

[0072] The following combination Figures 3-7 This application provides an example of a radar-based distance detection method.

[0073] Figure 3 This diagram illustrates the range-time relationship during a radar approaching a target at a constant speed.

[0074] For example, the distance includes both the historical target distance and the distance corresponding to the first signal.

[0075] For example, the first signal belongs to multiple scattered signals, and the signal-to-noise ratio of the first signal is greater than a first preset threshold.

[0076] For example, multiple scattered signals are radar detection signals scattered by multiple objects. The radar detection signals are the electromagnetic waves emitted by the radar that serve a detection function.

[0077] Specifically, because the radar is approaching the target at a constant speed, the distance between the radar and the target has a certain linear relationship with time. The first signal that does not conform to this linear relationship (see...) Figure 3 The numbers 310 and 320 in the text should be noise.

[0078] Therefore, the target signal can be determined by judging whether the first signal satisfies the motion trend of the radar relative to the target object.

[0079] For example, the target signal is the radar detection signal scattered by the target object.

[0080] Figure 4 This diagram illustrates the range-time-signal-noise ratio relationship during a radar approaching a target at a constant speed.

[0081] See Figure 4 As can be seen, the closer the radar is to the target, the higher the signal-to-noise ratio of the target signal. Therefore, the target signal can be determined by judging whether the first signal conforms to the law of increasing energy.

[0082] For example, the energy increase law is that the signal-to-noise ratio of the target signal is negatively correlated with the target distance corresponding to the target signal.

[0083] Therefore, based on the conditions for judging target signals in current range detection methods (i.e., determining the first signal as the target signal), this application adds the following discrimination condition: the first signal that conforms to the radar's motion trend and energy increase law relative to the target object is determined as the target signal.

[0084] Under the conditions for determining the target signal provided in this application, the false alarm probability of the target signal can be obtained by the following formula:

[0085]

[0086] Where P1 is the linear compliance probability and P2 is the compliance probability of the energy increasing law.

[0087] For example, if the radar approaches the target object at a constant speed, the linear coincidence probability can be calculated using the following formula:

[0088]

[0089] Where N is the number of range gates included in the observation range window, and n is the number of sampling points that continuously match the radar's motion trend relative to the target object.

[0090] For example, if a radar has a range threshold of 0.5m and an observation range window of 5m, then N is 10. If the third, fourth, and fifth points out of the 10 observed sampling points match the radar's movement relative to the target object, then n is 3.

[0091] For example, if the radar approaches the target object at a constant speed, the probability of matching the energy increase pattern can be calculated using the following formula:

[0092]

[0093] Where n is the number of sampling points that continuously conform to the law of increasing energy.

[0094] Based on the above formula, a false alarm probability of 10 is plotted. -12 At that time, the relationship curve between the detection probability of the target signal and the first preset threshold determined according to the current distance detection method and the method according to this application is shown in the figure. Figure 5 Curve 510 shows the relationship between the detection probability of the target signal determined by the current distance detection method and the first preset threshold, while curve 520 shows the relationship between the detection probability of the target signal determined by the method of this application and the first preset threshold. By comparison... Figure 5 As can be observed from curves 510 and 520, under the same false alarm probability and with the same first preset threshold, the detection probability of the target signal determined by the method of this application is greater.

[0095] Figure 6 This application illustrates a radar-based distance detection method 600, which can be applied to radar. This is an example and not a limitation. Method 600 may include steps S601-S603, which will be described below.

[0096] S601, determine the signal-to-noise ratio of the received multiple scattered signals.

[0097] Specifically, the received multiple scattered signals can be subjected to a fast Fourier transform to obtain the frequency domain data corresponding to the multiple scattered signals. Then, the frequency domain data corresponding to the multiple scattered signals can be processed by background noise statistics and signal extraction to separate the background noise energy and signal energy of each scattered signal. The ratio of background noise energy to signal energy is the signal-to-noise ratio of the scattered signal.

[0098] In one example, if the target object moves slowly and the chirping signal lasts a long time, and the MCU has spare computing resources, the signal-to-noise ratio of all received scattered signals can be determined.

[0099] In another example, if the MCU has limited computing resources or there is a chirp signal period, the signal-to-noise ratio of the scattered signal can be determined only within a preset range.

[0100] S602 determines the current target signal from multiple scattered signals based on the signal-to-noise ratio of multiple scattered signals, the signal-to-noise ratio of multiple historical target signals, and the distance of multiple historical targets.

[0101] In one possible implementation, at least one first signal from a plurality of scattered signals can be identified. Then, based on the signal-to-noise ratios of the plurality of scattered signals, the signal-to-noise ratios of the plurality of historical target signals, and the distances of the plurality of historical targets, it is determined whether the first signal conforms to the motion trend and energy increase law of the radar relative to the target object. The first signal that conforms to the motion trend and energy increase law of the radar relative to the target object is determined as the target signal.

[0102] In one example, the historical target signal and the first signal can be arranged in descending order of target distance to obtain a first sequence. Then, by judging whether the signal-to-noise ratio of the first signal in the first sequence conforms to an increasing trend, it can be determined whether the first signal conforms to the energy increasing law. By judging whether the distance-time relationship of the first signal in the first sequence conforms to the speed and direction of the radar relative to the target object, it can be determined whether the first signal conforms to the movement trend of the radar relative to the target object.

[0103] For example, there are 5 identified first signals, which can be denoted as D1, D2, D3, D4, and D5. There are 12 historical target signals, denoted as L1, L2, L3, L4, L5, L6, L7, L8, L9, L10, L11, and L12. Arranging these signals in descending order of their corresponding target distances yields the following first sequence: L1, L2, L3, D1, L4, L5, L6, D3, L7, L8, L9, D4, L10, L11, L12, D2, and D5.

[0104] The table below shows the detection time corresponding to the historical target signal and the first signal in the first sequence, the historical target distance corresponding to the historical target signal and the distance corresponding to the first signal, and the signal-to-noise ratio of the historical target signal and the first signal:

[0105] L1 L2 L3 D1 L4 L5 Distance (m) 30 28 26 25 24 22 Signal-to-noise ratio (dB) 100 105 120 160 180 190 Time (s) 0 1 2 12 3 4 L6 D3 L7 L8 L9 D4 Distance (m) 20 19 18 16 14 13 Signal-to-noise ratio (dB) 200 205 250 290 360 350 Time (s) 5 12 6 7 8 12 L10 L11 L12 D2 D5 Distance (m) 12 10 8 6 3 Signal-to-noise ratio (dB) 390 450 600 800 850 Time (s) 9 10 11 12 12

[0106] According to the table above, it can be observed that the target object and the radar are approaching at a constant speed. The target distances corresponding to the first signals D1, D3, and D4 are all greater than the historical target distances corresponding to the historical target signals at the previous moment (8m), which does not conform to the radar's direction of motion relative to the target object. The distance corresponding to the first signal D5 does not conform to the radar's speed of motion relative to the target object. The signal-to-noise ratio corresponding to the first signal D4 does not conform to the energy increase law. Therefore, the first signal D2 is determined to be the target signal.

[0107] In another example, a time-distance-signal-noise ratio curve can be plotted between the historical target signals and the first signal within a preset time period, based on the signal-to-noise ratios of multiple historical target signals and the distances to multiple historical targets. The target signal can then be determined based on this time-distance-signal-noise ratio curve.

[0108] For example, based on the same data in the example above, plot as follows: Figure 7 The time-distance-signal-noise ratio curve is shown. It can be observed that the first signals D1, D3, D4, and D5 do not conform to the trend of the curve, so the first signal D2 is determined as the target signal.

[0109] S603, determine the current target distance of the target object based on the current target signal.

[0110] Specifically, after determining the current target signal, the distance corresponding to the current target signal can be determined as the current target distance.

[0111] For example, the current target distance is the distance between the current target object and the radar.

[0112] According to the method provided in this application, by expanding the range gate and determining the target signal based on historical target signals and multiple scattered signals, the amount of data available for judging the target signal can be increased, thereby improving the detection probability. Furthermore, because the computational load of the method used in this application in determining the current target signal is much less than that of algorithms such as track initiation, the method of this application can achieve real-time target tracking while improving the detection probability.

[0113] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0114] Corresponding to the radar-based distance detection method in the above embodiments, Figure 7 A structural block diagram of a radar detection device provided in an embodiment of this application is shown. For ease of explanation, only the parts related to the embodiment of this application are shown.

[0115] Reference Figure 8 The device includes: a processing unit 810;

[0116] Processing unit 810 can be used for:

[0117] Determine the signal-to-noise ratio of the received multiple scattered signals, wherein the multiple scattered signals are detection signals of the radar scattered by multiple objects;

[0118] Based on the signal-to-noise ratio of the plurality of scattered signals, the signal-to-noise ratio of the plurality of historical target signals, and the distances of the plurality of historical targets, a current target signal is determined from the plurality of scattered signals. The target signal is the radar detection signal scattered by the target object. The plurality of historical target signals are the detection signals scattered by the target object before reaching the current position. The plurality of historical target distances are the distances between the target object and the radar before reaching the current position.

[0119] The current target distance is determined based on the current target signal, where the target distance is the distance between the target object and the radar.

[0120] In one example, the processing unit 810 may specifically be used to: determine at least one first signal among multiple scattered signals; then, based on the signal-to-noise ratio of the multiple scattered signals, the signal-to-noise ratio of multiple historical target signals, and the distances to multiple historical targets, determine whether the first signal conforms to the energy increase law and the motion trend of the radar relative to the target object. The first signal that conforms to the energy increase law and the motion trend of the radar relative to the target object is determined as the current target signal.

[0121] For example, the signal-to-noise ratio of the first signal is greater than a first preset threshold.

[0122] For example, the energy increase law is that the signal-to-noise ratio of the target signal is negatively correlated with the target distance corresponding to the target signal.

[0123] In one example, the processing unit 810 can specifically be used to: arrange at least one first signal and historical target signals in descending order of target distance to obtain a first sequence. By determining whether the signal-to-noise ratio of the first signal in the first sequence conforms to an increasing trend, it can be determined whether the first signal conforms to an increasing energy law; by determining whether the distance-time relationship of the first signal in the first sequence conforms to the radar's speed and direction of motion relative to the target object, it can be determined whether the first signal conforms to the radar's motion trend relative to the target object.

[0124] In another example, the processing unit 810 can specifically be used to: plot the time-range-signal-noise ratio curve of historical target signals within a preset time period based on the signal-to-noise ratio of multiple historical target signals and the distances of multiple historical targets; and determine, based on the time-range-signal-noise ratio curve, whether the first signal conforms to the energy increase law and the motion trend of the radar relative to the target object.

[0125] This application provides a radar-based range detection method. Compared to current range detection methods, this application expands the range gate range by determining the target signal based on historical target signals and multiple scattered signals. This increases the amount of data available for target signal determination and improves the detection probability. Because the computational load for determining the current target signal using the method in this application is much less than that of algorithms such as track initiation, it can achieve real-time target tracking while improving the detection probability.

[0126] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0127] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments 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. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0128] Figure 9 The diagram shown is a structural schematic of a radar detection device provided in one embodiment of this application. Figure 9 The radar detection device 900 shown may include: at least one processor 910 Figure 9 The diagram shows only one processor, memory 920, and computer program 930 stored in memory 920 and executable on at least one processor 910. When processor 910 executes computer program 930, it implements the steps in any of the above method embodiments.

[0129] The processing device 900 can be a robot or other processing device capable of implementing the above methods. This application embodiment does not impose any restrictions on the specific type of processing device.

[0130] Those skilled in the art will understand that Figure 9 This is merely an example of processing device 900 and does not constitute a limitation on the processing device. It may include more or fewer components than shown, or combine certain components, or use different components. For example, the processing device 900 may also include input / output interfaces.

[0131] The processor 910 may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0132] In some embodiments, memory 920 may be an internal storage unit, such as a hard disk or RAM. In other embodiments, memory 920 may be an external storage device, such as a plug-in hard disk, a smart media card (SMC), a secure digital card (SD), or a flash card. Furthermore, memory 920 may include both internal and external storage units. Memory 920 is used to store operating systems, applications, bootloaders, data, and other programs, such as program code for computer programs. Memory 920 may also be used to temporarily store data that has been output or will be output.

[0133] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0134] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments 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. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0135] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps described in the various method embodiments above.

[0136] This application provides a computer program product that, when run on a radar detection device, enables the radar detection device to perform the steps described in the above-described method embodiments.

[0137] If the integrated unit 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, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. A computer-readable medium can include at least: any entity or device capable of carrying computer program code to a photographic device / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0138] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0139] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

Claims

1. A radar-based distance detection method, characterized in that, include: Determine the signal-to-noise ratio of the multiple received scattered signals, wherein the multiple scattered signals are detection signals of the radar scattered by multiple objects; Based on the signal-to-noise ratio of the plurality of scattered signals, the signal-to-noise ratio of the plurality of historical target signals, and the plurality of historical target distances, the current target signal is determined from the plurality of scattered signals. The target signal is the radar detection signal scattered by the target object. The plurality of historical target signals are the radar detection signals scattered by the target object before reaching the current position. The plurality of historical target distances are the distances between the target object and the radar before reaching the current position. The current target distance is determined based on the current target signal, where the current target distance is the distance between the target object and the radar. The step of determining the current target signal from the plurality of scattered signals based on the signal-to-noise ratio of the plurality of scattered signals, the signal-to-noise ratio of the plurality of historical target signals, and the distances of the plurality of historical targets includes: Determine at least one first signal among the plurality of scattering signals, wherein the signal-to-noise ratio of the first signal is greater than a first preset threshold; Based on the signal-to-noise ratio of the multiple scattered signals, the signal-to-noise ratio of the multiple historical target signals, and the distances of the multiple historical targets, it is determined whether the first signal conforms to the energy increase law and the motion trend of the radar relative to the target object. The energy increase law is that the signal-to-noise ratio of the target signal is negatively correlated with the target distance corresponding to the target signal. The first signal that conforms to the energy increase law and the motion trend of the radar relative to the target object is determined as the target signal.

2. The method as described in claim 1, characterized in that, The step of determining whether the first signal conforms to the energy increase law and the motion trend of the radar relative to the target object based on the signal-to-noise ratio of the multiple scattered signals, the signal-to-noise ratio of the multiple historical target signals, and the distance of the multiple historical targets includes: Arrange the at least one first signal and the historical target signal in descending order according to the target distance to obtain a first sequence; By determining whether the signal-to-noise ratio of the first signal in the first sequence conforms to an increasing trend, it can be determined whether the first signal conforms to the energy increasing law. By determining whether the distance-time relationship of the first signal in the first sequence conforms to the speed and direction of the radar relative to the target object, it can be determined whether the first signal conforms to the movement trend of the radar relative to the target object.

3. The method as described in claim 1, characterized in that, The step of determining whether the first signal conforms to the energy increase law and the motion trend of the radar relative to the target object based on the signal-to-noise ratio of the multiple scattered signals, the signal-to-noise ratio of the multiple historical target signals, and the distance of the multiple historical targets includes: Based on the signal-to-noise ratio of the multiple historical target signals and the distances to the multiple historical targets, plot the time-distance-signal-noise ratio curve of the historical target signals within a preset time period; Based on the time-range-signal-noise ratio curve, determine whether the first signal conforms to the energy increase law and the motion trend of the radar relative to the target object.

4. A radar detection device, characterized in that, include: Processing unit; The processing unit is used for: Determine the signal-to-noise ratio of the multiple received scattered signals, wherein the multiple scattered signals are detection signals of the radar scattered by multiple objects; Based on the signal-to-noise ratio of the plurality of scattered signals, the signal-to-noise ratio of the plurality of historical target signals, and the plurality of historical target distances, the current target signal is determined from the plurality of scattered signals. The target signal is the radar detection signal scattered by the target object. The plurality of historical target signals are the radar detection signals scattered by the target object before reaching the current position. The plurality of historical target distances are the distances between the target object and the radar before reaching the current position. The current target distance is determined based on the current target signal, where the target distance is the distance between the target object and the radar. The processing unit is specifically used for: Determine at least one first signal among the plurality of scattering signals, wherein the signal-to-noise ratio of the first signal is greater than a first preset threshold; Based on the signal-to-noise ratio of the multiple scattered signals, the signal-to-noise ratio of the multiple historical target signals, and the distances of the multiple historical targets, it is determined whether the first signal conforms to the energy increase law and the motion trend of the radar relative to the target object. The energy increase law is that the signal-to-noise ratio intensity of the target signal is negatively correlated with the target distance corresponding to the target signal. The first signal that conforms to the energy increase law and the motion trend of the radar relative to the target object is determined as the current target signal.

5. The apparatus as described in claim 4, characterized in that, The processing unit is specifically used for: Arrange the at least one first signal and the historical target signal in descending order according to the target distance to obtain a first sequence; By determining whether the signal-to-noise ratio of the first signal in the first sequence conforms to an increasing trend, it can be determined whether the first signal conforms to the energy increasing law. By determining whether the distance-time relationship of the first signal in the first sequence conforms to the speed and direction of the radar relative to the target object, it can be determined whether the first signal conforms to the movement trend of the radar relative to the target object.

6. The apparatus as claimed in claim 4, characterized in that, The processing unit is specifically used for: Based on the signal-to-noise ratio of the multiple historical target signals and the distances to the multiple historical targets, plot the time-distance-signal-noise ratio curve of the historical target signals within a preset time period; Based on the time-range-signal-noise ratio curve, determine whether the first signal conforms to the energy increase law and the motion trend of the radar relative to the target object.

7. A radar detection device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method as described in any one of claims 1 to 3.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 3.

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