Radar signal processing method and device of unmanned aerial vehicle, electronic equipment and storage medium

Abstract

The application provides a radar signal processing method and device of a UAV, electronic equipment and a storage medium. The method comprises: acquiring a current height of the UAV; performing interference filtering processing on original echo signals collected by a radar of the UAV according to calibration information corresponding to the current height, to obtain filtered available echo signals, wherein the calibration information is used to represent echo signal characteristics of the radar in a preset bottom noise environment. Based on the calibration information, interference information such as obstacles other than the bottom noise environment itself can be identified from the original echo signals, so that accurate interference signal filtering can be realized, thereby avoiding abnormal conditions of the UAV. In addition, different heights have corresponding calibration information, which can ensure high matching degree of the calibration information and the current height, and further ensure the accuracy of interference signal filtering.

Description

Technical Field

[0001] This application relates to the field of unmanned aerial vehicle (UAV) technology, and more specifically, to a radar signal processing method, apparatus, electronic device, and storage medium for UAVs. Background Technology

[0002] During operational flights, drones need to collect signals using radar on board, and then use these signals to perform functions such as target identification, point cloud mapping, and obstacle avoidance. Since the raw radar signals contain interference signals generated by the drone itself, it is necessary to filter out these interference signals to obtain the valid signals, which are then used for subsequent target identification and other processing.

[0003] In existing technologies, interference signals are mainly filtered out by setting parameter thresholds for various operating parameters of the drone.

[0004] However, using existing technologies may not be able to accurately filter out interference signals in some working scenarios, leading to abnormal operation of the drone. Summary of the Invention

[0005] One of the purposes of this application is to provide a radar signal processing method, device, electronic device and storage medium for unmanned aerial vehicles (UAVs) to solve the problem of abnormal UAV operation caused by the inability to accurately filter out interference signals in the prior art.

[0006] In a first aspect, this application provides a radar signal processing method for an unmanned aerial vehicle (UAV), comprising:

[0007] Obtain the drone's current altitude;

[0008] Based on the calibration information corresponding to the current altitude, interference filtering is performed on the original echo signal collected by the UAV's radar to obtain a filtered usable echo signal. The calibration information is used to characterize the radar echo signal characteristics in a preset low-noise environment.

[0009] As one possible implementation, the calibration information includes: a signal threshold curve, wherein the signal threshold curve is used to characterize the change in power of the radar echo signal with frequency in a preset noise floor environment;

[0010] The step of performing interference filtering on the raw echo signal collected by the UAV's radar based on the calibration information corresponding to the current altitude to obtain a filtered usable echo signal includes:

[0011] The original echo signal is subjected to spectral analysis to obtain the actual spectrum information;

[0012] The actual spectrum information is compared with the signal threshold curve corresponding to the current height to determine the frequency to be filtered out, wherein the power of the frequency to be filtered out in the actual spectrum information is less than the power on the signal threshold curve;

[0013] The echo signals belonging to the frequency to be filtered out in the original echo signal are filtered out to obtain the usable echo signal.

[0014] As one possible implementation, the calibration information includes: spectrum calibration parameters;

[0015] The step of performing interference filtering on the raw echo signal collected by the UAV's radar based on the calibration information corresponding to the current altitude to obtain a filtered usable echo signal includes:

[0016] Based on the spectral calibration parameters corresponding to the current height, the set original threshold curve is calibrated to obtain the signal threshold curve;

[0017] The original echo signal is subjected to interference filtering based on the signal threshold curve to obtain the usable echo signal.

[0018] As one possible implementation, the calibration information includes: spectrum calibration parameters;

[0019] The step of performing interference filtering on the raw echo signal collected by the UAV's radar based on the calibration information corresponding to the current altitude to obtain a filtered usable echo signal includes:

[0020] The original echo signal is calibrated according to the spectral calibration parameters corresponding to the current altitude to obtain the calibrated signal;

[0021] The calibrated signal is subjected to interference filtering by a set original threshold curve to obtain the usable echo signal.

[0022] As one possible implementation, the calibration information corresponding to different altitude ranges is obtained through pre-storage. The process of determining the calibration information corresponding to any altitude range includes:

[0023] The noise floor echo signal collected by the radar of the UAV when the UAV is located in the noise floor environment and within the target altitude range;

[0024] Based on the noise floor echo signal, determine the signal spectrum information corresponding to the target height range;

[0025] Based on the signal spectrum information, determine the spectrum calibration parameters;

[0026] Based on the spectral calibration parameters, calibration information corresponding to the target height range is generated, and the calibration information corresponding to the target height range is used as the calibration information corresponding to each height within the target height range.

[0027] As one possible implementation, determining the signal spectrum information corresponding to the target height range based on the background noise echo signal includes:

[0028] The number of sampling points is determined based on the pulse width and sampling period of the UAV's radar.

[0029] The frequency of each sampling point is determined based on the sampling frequency of the UAV's radar and the number of sampling points;

[0030] Spectral analysis was performed on the noise floor echo signal to obtain the power corresponding to the frequency of each sampling point;

[0031] Based on the frequency of each sampling point and the power corresponding to the frequency of each sampling point, the signal spectrum information corresponding to the target height range is obtained.

[0032] As one possible implementation, determining the spectrum calibration parameters based on the signal spectrum information includes:

[0033] Based on the signal spectrum information and the preset polynomial fitting coefficients, polynomial fitting processing is performed to obtain the fitted polynomial.

[0034] The coefficients in the fitted polynomial are used as the spectrum calibration parameters.

[0035] As one possible implementation, the step of performing polynomial fitting processing based on the signal spectrum information and preset polynomial fitting coefficients to obtain a fitted polynomial includes:

[0036] The signal spectrum information and the polynomial fitting coefficients are input into the target polynomial fitting model to obtain the fitted polynomial.

[0037] As one possible implementation, generating calibration information corresponding to the target altitude range based on the spectral calibration parameters includes:

[0038] Based on the spectral calibration parameters, a signal threshold curve corresponding to the target height range is generated.

[0039] As one possible implementation, generating the signal threshold curve corresponding to the target height range based on the spectral calibration parameters includes:

[0040] Based on the spectrum calibration parameters and the frequencies of each sampling point of the UAV's radar, a calibration curve corresponding to the target altitude range is generated;

[0041] Based on the calibration curve and the set original threshold curve corresponding to the target altitude range, the signal threshold curve corresponding to the target altitude range is obtained, wherein the original threshold curve is obtained based on the spectral analysis of the radar echo signal when the UAV is initially powered on.

[0042] As one possible implementation, generating the calibration curve corresponding to the target altitude range based on the spectrum calibration parameters and the frequencies of each sampling point of the UAV's radar includes:

[0043] Based on the spectral calibration parameters and the frequencies of each sampling point, a fitting process is performed to obtain the calibration curve corresponding to the target height range.

[0044] As one possible implementation, obtaining the signal threshold curve corresponding to the target height range based on the calibration curve and the set original threshold curve corresponding to the target height range includes:

[0045] The calibration curve is superimposed on the original threshold curve to obtain the signal threshold curve corresponding to the target height range.

[0046] As one possible implementation, the step of performing interference filtering processing on the raw echo signal collected by the UAV's radar based on the calibration information corresponding to the current altitude to obtain a filtered usable echo signal includes:

[0047] Based on the calibration information corresponding to the current altitude and the radar operating parameters corresponding to the current altitude, interference filtering is performed on the original echo signal collected by the UAV's radar to obtain the filtered usable echo signal.

[0048] Secondly, this application provides a radar signal processing device for an unmanned aerial vehicle (UAV), comprising:

[0049] The acquisition module is used to obtain the current altitude of the drone;

[0050] The filtering module is used to perform interference filtering on the original echo signal collected by the radar of the UAV according to the calibration information corresponding to the current altitude, so as to obtain the filtered usable echo signal. The calibration information is used to characterize the radar echo signal characteristics in a preset low-noise environment.

[0051] As one possible implementation, the calibration information includes: a signal threshold curve, wherein the signal threshold curve is used to characterize the change in power of the radar echo signal with frequency in a preset noise floor environment;

[0052] The filtering module is specifically used for:

[0053] The original echo signal is subjected to spectral analysis to obtain the actual spectrum information;

[0054] The actual spectrum information is compared with the signal threshold curve corresponding to the current height to determine the frequency to be filtered out, wherein the power of the frequency to be filtered out in the actual spectrum information is less than the power on the signal threshold curve;

[0055] The echo signals belonging to the frequency to be filtered out in the original echo signal are filtered out to obtain the usable echo signal.

[0056] As one possible implementation, the calibration information includes: spectrum calibration parameters;

[0057] The filtering module is specifically used for:

[0058] Based on the spectral calibration parameters corresponding to the current height, the set original threshold curve is calibrated to obtain the signal threshold curve;

[0059] The original echo signal is subjected to interference filtering based on the signal threshold curve to obtain the usable echo signal.

[0060] As one possible implementation, the calibration information includes: spectrum calibration parameters;

[0061] The filtering module is specifically used for:

[0062] The original echo signal is calibrated according to the spectral calibration parameters corresponding to the current altitude to obtain the calibrated signal;

[0063] The calibrated signal is subjected to interference filtering by a set original threshold curve to obtain the usable echo signal.

[0064] As one possible implementation, the calibration information corresponding to different altitude ranges is obtained through pre-stored data, and the filtering module is further used for:

[0065] The noise floor echo signal collected by the radar of the UAV when the UAV is located in the noise floor environment and within the target altitude range;

[0066] Based on the noise floor echo signal, determine the signal spectrum information corresponding to the target height range;

[0067] Based on the signal spectrum information, determine the spectrum calibration parameters;

[0068] Based on the spectral calibration parameters, calibration information corresponding to the target height range is generated, and the calibration information corresponding to the target height range is used as the calibration information corresponding to each height within the target height range.

[0069] As one possible implementation, the filtering module is specifically used for:

[0070] The number of sampling points is determined based on the pulse width and sampling period of the UAV's radar.

[0071] The frequency of each sampling point is determined based on the sampling frequency of the UAV's radar and the number of sampling points;

[0072] Spectral analysis was performed on the noise floor echo signal to obtain the power corresponding to the frequency of each sampling point;

[0073] Based on the frequency of each sampling point and the power corresponding to the frequency of each sampling point, the signal spectrum information corresponding to the target height range is obtained.

[0074] As one possible implementation, the filtering module is specifically used for:

[0075] Based on the signal spectrum information and the preset polynomial fitting coefficients, polynomial fitting processing is performed to obtain the fitted polynomial.

[0076] The coefficients in the fitted polynomial are used as the spectrum calibration parameters.

[0077] As one possible implementation, the filtering module is specifically used for:

[0078] The signal spectrum information and the polynomial fitting coefficients are input into the target polynomial fitting model to obtain the fitted polynomial.

[0079] As one possible implementation, the filtering module is specifically used for:

[0080] Based on the spectral calibration parameters, a signal threshold curve corresponding to the target height range is generated.

[0081] As one possible implementation, the filtering module is specifically used for:

[0082] Based on the spectrum calibration parameters and the frequencies of each sampling point of the UAV's radar, a calibration curve corresponding to the target altitude range is generated;

[0083] Based on the calibration curve and the set original threshold curve corresponding to the target altitude range, the signal threshold curve corresponding to the target altitude range is obtained, wherein the original threshold curve is obtained based on the spectral analysis of the radar echo signal when the UAV is initially powered on.

[0084] As one possible implementation, the filtering module is specifically used for:

[0085] Based on the spectral calibration parameters and the frequencies of each sampling point, a fitting process is performed to obtain the calibration curve corresponding to the target height range.

[0086] As one possible implementation, the filtering module is specifically used for:

[0087] The calibration curve is superimposed on the original threshold curve to obtain the signal threshold curve corresponding to the target height range.

[0088] As one possible implementation, the filtering module is specifically used for:

[0089] Based on the calibration information corresponding to the current altitude and the radar operating parameters corresponding to the current altitude, interference filtering is performed on the original echo signal collected by the UAV's radar to obtain the filtered usable echo signal.

[0090] Thirdly, this application provides an electronic device, including: a processor and a memory, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor executes the machine-readable instructions to perform the steps of the radar signal processing method for a drone as described in the first aspect above.

[0091] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, performs the steps of the radar signal processing method for a drone as described in the first aspect above.

[0092] The radar signal processing method, apparatus, electronic device, and storage medium for unmanned aerial vehicles (UAVs) provided in this application, after acquiring the current altitude of the UAV, can perform interference filtering on the raw echo signal collected by the UAV's radar based on the calibration information corresponding to the current altitude. Since the calibration information can characterize the echo signal features of the radar in a preset noise floor environment, it can represent the characteristics of the noise floor environment itself. Therefore, based on this calibration information, interference information such as obstacles, other than the noise floor environment itself, can be identified from the raw echo signal, thereby achieving accurate interference signal filtering and preventing abnormal situations from occurring with the UAV. Furthermore, different altitudes have corresponding calibration information, ensuring a high degree of matching between the calibration information and the current altitude, further guaranteeing the accuracy of interference signal filtering. Attached Figure Description

[0093] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0094] Figure 1 A schematic flowchart illustrating the radar signal processing method for an unmanned aerial vehicle (UAV) provided in an embodiment of this application;

[0095] Figure 2 This is a schematic diagram of the interference filtering process based on the signal threshold curve;

[0096] Figure 3 A flowchart illustrating the process for determining calibration information for any given altitude range;

[0097] Figure 4 A flowchart illustrating the process of determining the signal spectrum information corresponding to the target altitude range;

[0098] Figure 5 This is a schematic diagram of the pulse width and sampling period of a drone.

[0099] Figure 6 A flowchart illustrating the process of generating signal threshold curves corresponding to the target height range;

[0100] Figure 7 A modular structure diagram of the radar signal processing device for an unmanned aerial vehicle provided in an embodiment of this application;

[0101] Figure 8 This is a schematic diagram of the structure of an electronic device 800 provided in an embodiment of this application. Detailed Implementation

[0102] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the accompanying drawings in this application are for illustrative and descriptive purposes only and are not intended to limit the scope of protection of this application. Furthermore, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of this application. It should be understood that the operations in the flowcharts may not be implemented in sequence, and steps without logical contextual relationships may be reversed or implemented simultaneously. In addition, those skilled in the art, guided by the content of this application, may add one or more other operations to the flowcharts, or remove one or more operations from the flowcharts.

[0103] Furthermore, the described embodiments are merely some, not all, of the embodiments of this application. The components of the embodiments of this application described and illustrated herein can typically be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0104] Currently, interference signal filtering is mainly achieved by setting threshold values ​​for various operational parameters of the drone. For example, a blind zone range can be pre-defined for the drone, within which it will not collect and record radar point cloud data. Another example is setting a signal-to-noise ratio (SNR) threshold; only signals with a SNR strength higher than this threshold are considered valid, while signals with a SNR strength less than or equal to the threshold are filtered out. However, these methods may fail to accurately filter interference signals as the drone's operational environment changes, potentially leading to operational anomalies. For instance, while a blind zone range is effective for low-altitude plant protection operations such as fertilizer application or pesticide spraying, it is completely different when the drone is operating in high-altitude terrain mapping. The noise information to be filtered out also differs. If the same blind zone range is applied as in low-altitude plant protection, the drone may misidentify obstacles and hover abnormally.

[0105] This application proposes a radar signal processing method for unmanned aerial vehicles (UAVs) to address the aforementioned issues. By utilizing calibration information obtained in advance in noise-based environments at various altitudes, interference is filtered out from the radar signal at the current altitude. Since the noise performance at different altitudes is taken into account, accurate interference signal filtering can be achieved, thereby preventing abnormal situations from occurring with the UAV.

[0106] The embodiments of this application can be applied to any operational scenario of drones, such as the aforementioned low-altitude plant protection work scenario of spreading fertilizer or spraying pesticides, or the aforementioned high-altitude work scenario of terrain mapping. In any operational scenario, the drone can execute the method steps of the embodiments of this application in real time to achieve real-time interference signal filtering.

[0107] Figure 1This is a flowchart illustrating a radar signal processing method for a drone provided in an embodiment of this application. The executing entity of this method can be, for example, a drone equipped with radar for signal acquisition. Alternatively, the executing entity can also be other electronic devices controlling the drone's flight. For ease of description, the following embodiments use a drone as an example for illustration. Figure 1 As shown, the method includes:

[0108] S101. Obtain the current altitude of the drone.

[0109] Optionally, after the drone starts flying, its current altitude can be obtained in real time. Optionally, the drone can obtain its current altitude using onboard hardware such as ultrasonic devices, barometers, GPS modules, millimeter-wave radar, or lidar. Alternatively, it can obtain its current altitude by performing image recognition on ground images captured by the drone's camera. Alternatively, it can combine the results from hardware acquisition with the results from software image recognition to determine the current altitude. The choice can be flexible and tailored to the specific needs.

[0110] Optionally, the current altitude of the drone at the current moment can refer to the drone's current altitude above the ground.

[0111] S102. Based on the calibration information corresponding to the current altitude, the original echo signal collected by the UAV's radar is subjected to interference filtering to obtain the filtered usable echo signal. The calibration information is used to characterize the radar echo signal characteristics in a preset noise floor environment.

[0112] Optionally, different altitudes can have corresponding calibration information to ensure that calibration information matching that altitude can be used at different altitudes. For example, when the drone's altitude is 100 meters, the calibration information corresponding to altitude 100 meters is used. When the drone's altitude is 200 meters, the calibration information corresponding to altitude 200 meters is used.

[0113] Optionally, if the above calibration information characterizes the radar echo signal characteristics in a preset noise floor environment, then the corresponding calibration information at the current altitude can characterize the radar echo signal characteristics at the current altitude in the preset noise floor environment.

[0114] Optionally, the aforementioned preset noise floor environment can refer to an environment with flat ground, open space, and no obstacles. In this noise floor environment, the radar echo signal can represent the characteristics of the environment itself, without being mixed with the characteristics of additional obstacles.

[0115] Optionally, radar echo signals can be pre-collected at different altitudes within the aforementioned noisy environment, and calibration information corresponding to different altitudes can be obtained by analyzing the radar echo signals. This calibration information can then be stored in the UAV. During UAV flight operations, whenever the UAV reaches a certain altitude, the calibration information corresponding to that altitude can be read, and interference filtering can be performed on the raw echo signals collected by the UAV's radar based on this calibration information. It should be understood that the raw echo signals collected by the radar refer to the raw echo signals collected by the radar at the current time and current altitude.

[0116] After using the aforementioned calibration information to filter out interference from the raw echo signal collected by the radar, a usable echo signal can be obtained. The UAV can then analyze this usable echo signal to perform target identification, point cloud mapping, obstacle avoidance, and other functions.

[0117] In this embodiment, after obtaining the current altitude of the UAV, interference filtering can be performed on the raw echo signal collected by the UAV's radar based on the calibration information corresponding to the current altitude. Since the calibration information can characterize the radar echo signal features in a preset noise floor environment, it can represent the characteristics of the noise floor environment itself. Therefore, based on this calibration information, interference information such as obstacles, other than the noise floor environment itself, can be identified from the raw echo signal, thereby achieving accurate interference signal filtering and preventing abnormal situations from occurring with the UAV. Furthermore, different altitudes have corresponding calibration information, ensuring a high degree of matching between the calibration information and the current altitude, further guaranteeing the accuracy of interference signal filtering.

[0118] Optionally, the calibration information described above can take different forms. In one optional approach, the calibration information can be a signal threshold curve pre-established based on the background noise environment. In another optional approach, the calibration information can be spectral calibration parameters. The interference filtering process under these two methods will be explained below.

[0119] Figure 2 This is a flowchart illustrating interference filtering based on a signal threshold curve, as shown below. Figure 2 As shown, one possible approach to step S102 above includes:

[0120] S201. Perform spectral analysis on the original echo signal to obtain the actual spectrum information.

[0121] For example, a distance spectrum analysis can be performed on the original echo signal to obtain the corresponding actual spectral information. It should be understood that other types of spectral analysis can also be performed on the original echo signal to obtain the corresponding type of actual spectral information.

[0122] S202. Compare the actual spectrum information with the signal threshold curve corresponding to the current height to determine the frequency to be filtered out, wherein the power of the frequency to be filtered out in the actual spectrum information is less than the power on the signal threshold curve.

[0123] Optionally, the aforementioned signal threshold curve is used to characterize the change in radar echo signal power with frequency in a preset noise floor environment. Specifically, different altitudes have corresponding signal threshold curves.

[0124] The aforementioned actual spectrum information represents the variation of radar echo signal power with frequency at the current time and altitude. Therefore, both the horizontal axis of the signal threshold curve and the horizontal axis of the actual spectrum information represent frequency, while the vertical axis represents power. During comparison, frequencies on the horizontal axis can be compared one by one. For a given frequency, if the power of that frequency in the actual frequency information is less than the power of that frequency on the signal threshold curve, it indicates that the power of that frequency at the current time and altitude is less than its power in a noisy environment, falling into the category of interference signals.

[0125] S203. Filter out the echo signals belonging to the frequencies to be filtered out from the original echo signals to obtain the usable echo signals.

[0126] The power of the frequency to be filtered determined by the above steps is relatively small. Therefore, the echo signal at the frequency to be filtered is an interference signal to be filtered. Thus, the echo signal at the frequency to be filtered can be filtered out as an interference signal from the original echo signal, thereby obtaining the usable echo signal after interference filtering.

[0127] In this embodiment, by comparing the actual spectrum information of the current altitude with the signal threshold curve corresponding to the current altitude, the frequency to be filtered out can be accurately identified, and then the echo signal belonging to the frequency to be filtered out in the original echo signal can be filtered out, thereby ensuring the accuracy of interference signal filtering.

[0128] The interference filtering process is explained below when the calibration information is the frequency calibration parameters mentioned above.

[0129] Optionally, the aforementioned frequency calibration parameters can be parameters pre-generated based on the echo signal of the noise-scarce environment, capable of characterizing the radar echo signal at the current altitude within a preset noise-scarce environment. Pre-storing the aforementioned frequency calibration parameters in the UAV and using them for interference filtering in step S102 can significantly reduce the storage space occupied by the UAV while ensuring effective interference filtering. When the calibration information is the aforementioned frequency calibration parameters, interference filtering can be performed in any of the following ways during step S102.

[0130] In the first method, the original threshold curve can be calibrated according to the spectral calibration parameters corresponding to the current altitude to obtain the signal threshold curve. Then, interference filtering is performed on the original echo signal based on the signal threshold curve to obtain the usable echo signal.

[0131] Optionally, the aforementioned initial threshold curve can be a threshold curve obtained by performing spectral analysis on the radar echo signal when the UAV is initially powered on. This initial threshold curve can characterize the change in power of the radar echo signal with frequency when the UAV is initially powered on. For example, the horizontal axis of this initial threshold curve represents frequency, and the vertical axis represents power. Different altitudes have corresponding initial threshold curves.

[0132] Based on the obtained spectral calibration parameters and original threshold curve corresponding to the current altitude, a calibration curve corresponding to the current altitude can first be generated based on the spectral calibration parameters. Then, this calibration curve is superimposed on the original threshold curve to obtain a signal threshold curve, which is the same as the signal threshold curve used in the aforementioned steps S201-S203. Therefore, the process of interference filtering of the original echo signal based on this signal threshold curve is the same as the aforementioned steps S201-S203, and can be referred to the aforementioned embodiment, which will not be repeated here.

[0133] In this embodiment, only the spectrum calibration parameters are stored in the UAV in advance, and the signal threshold curve is restored using the spectrum calibration parameters and the original threshold curve and used for interference filtering, thereby reducing the storage space occupied by the UAV while ensuring the interference filtering effect.

[0134] In the second method, the original echo signal can be calibrated according to the spectral calibration parameters corresponding to the current altitude to obtain a calibrated signal. This calibrated signal is then subjected to interference filtering using a set original threshold curve to obtain the usable echo signal.

[0135] Optionally, since the spectrum calibration parameter corresponding to the current altitude can characterize the radar echo signal at the current altitude in a preset noise floor environment, the original echo signal can be directly calibrated using this spectrum calibration parameter to obtain a calibrated signal. For example, filtering and transforming the original echo signal using this spectrum calibration parameter can yield a calibrated signal. Based on this, interference filtering processing is performed on the calibrated signal using the original threshold curve to obtain the usable echo signal.

[0136] In this embodiment, only the spectrum calibration parameters are stored in the UAV in advance, and the original echo signal is calibrated using the spectrum calibration parameters before interference filtering is performed, thereby reducing the storage space occupied by the UAV while ensuring the interference filtering effect.

[0137] As mentioned earlier, different altitudes can have corresponding calibration information. In practical implementation, to reduce processing complexity, minimize storage space usage, and improve processing efficiency, multiple altitude ranges can be pre-divided, and calibration information corresponding to each altitude range can be determined. The calibration information for each altitude range is stored in the drone. That is, the calibration information corresponding to different altitude ranges is obtained through pre-storage. In actual use, when the drone flies to a certain altitude, the calibration information used is the calibration information corresponding to the altitude range in which that altitude is located. For example, multiple altitude ranges can be pre-divided at 10-meter intervals. For instance, 0 to 10 meters is one altitude range, called altitude range 1; 11 meters to 20 meters is another altitude range, called altitude range 2, and so on. Taking altitude range 2 as an example, when the drone flies to any altitude within altitude range 2, the calibration information corresponding to altitude range 2 is used for interference filtering. It should be understood that the smaller the range of the altitude range, the higher the accuracy of the corresponding calibration information. In practical implementation, the range of the altitude range can be flexibly set according to actual needs.

[0138] The following describes the process for determining calibration information corresponding to any altitude range. Optionally, this determination process can be performed in advance to obtain calibration information and store it in the UAV.

[0139] Figure 3 A flowchart illustrating the process for determining calibration information for any given altitude range is shown below. Figure 3 As shown, the process for determining the calibration information corresponding to any altitude range includes:

[0140] S301. Obtain the noise floor echo signal collected by the drone's radar when the drone is located in the aforementioned noise floor environment and within the target altitude range.

[0141] Optionally, the target altitude range can be any one of a pre-divided range of altitude ranges. That is, for each altitude range, the calibration information corresponding to that altitude range can be determined through the process of this embodiment.

[0142] Optionally, the drone can be controlled to fly in the aforementioned low-noise environment and maintain its flight altitude within the aforementioned target altitude range. When the drone flies within the aforementioned target altitude range, the echo signal collected by the drone's radar is acquired, and this echo signal is the aforementioned low-noise echo signal.

[0143] S302. Based on the aforementioned noise floor echo signal, determine the signal spectrum information corresponding to the aforementioned target height range.

[0144] Optionally, by analyzing the aforementioned noise floor echo signal, the signal spectrum information corresponding to the target altitude range can be obtained. This signal spectrum information can be, for example, the aforementioned range spectrum information, which can represent the variation of the noise floor signal power with frequency within the aforementioned noise floor environment and target altitude range. The specific process for determining the signal spectrum information will be described in the following embodiments.

[0145] S303. Based on the above signal spectrum information, determine the spectrum calibration parameters.

[0146] Optionally, the signal spectrum information can be fitted using a preset fitting model to obtain the aforementioned spectrum calibration parameters. The specific process will be described in the following embodiments.

[0147] S304. Based on the above-mentioned spectrum calibration parameters, generate calibration information corresponding to the above-mentioned target height range, and use the calibration information corresponding to the above-mentioned target height range as the calibration information corresponding to each height within the above-mentioned target height range.

[0148] In one scenario, if the calibration information is the aforementioned signal threshold curve, then in this step, a signal threshold curve can be generated based on the spectral calibration parameters. The specific generation process will be described in the following embodiments.

[0149] In another scenario, if the calibration information is the aforementioned spectrum calibration parameters, then in this step, the spectrum calibration parameters are directly used as the calibration information corresponding to the target altitude range, and the calibration information is stored in the UAV for interference filtering.

[0150] It should be understood that after obtaining the calibration information corresponding to the target height range, the calibration information corresponding to all heights within that target height range is obtained.

[0151] In this embodiment, by determining the signal spectrum information of the background noise echo signal in the background noise environment and determining the spectrum calibration parameters based on the signal spectrum information, calibration information that accurately characterizes the background noise environment can be obtained.

[0152] The method for determining the signal spectrum information corresponding to the target altitude range in step S302 above will be explained below.

[0153] Figure 4 A flowchart illustrating the process of determining the signal spectrum information corresponding to the target altitude range, as shown below. Figure 4 As shown, one possible approach to step S302 above includes:

[0154] S401. Determine the number of sampling points based on the pulse width and sampling period of the UAV's radar.

[0155] Figure 5This is a schematic diagram of the pulse width and sampling period of a drone, as shown below. Figure 5 As shown, the width of a pulse signal emitted by the radar is the aforementioned pulse width, which is determined by T. p This indicates that, simultaneously, the radar's sampling period is determined by T. s express.

[0156] Optionally, the number of sampling points can be calculated using the following formula (1).

[0157]

[0158] Where N is the number of sampling points, T p T is the pulse width. s The sampling period.

[0159] S402. Determine the frequency of each sampling point based on the sampling frequency of the UAV's radar and the number of sampling points mentioned above.

[0160] Wherein, the sampling frequency is the reciprocal of the sampling period, and the sampling frequency is expressed as f. s The frequency of each sampling point can be calculated using the following formula (2).

[0161]

[0162] Where f is the frequency of sampling point n, n is any single sampling point, n = 1, 2, ..., N, and N is the number of sampling points. s The sampling frequency.

[0163] S403. Perform spectral analysis on the above-mentioned low-noise echo signal to obtain the power corresponding to the frequency of each sampling point.

[0164] For example, distance spectrum analysis can be performed on the aforementioned low-noise echo signal to obtain the power corresponding to the frequency of each sampling point.

[0165] S404. Based on the frequency of each sampling point and the power corresponding to the frequency of each sampling point, obtain the signal spectrum information corresponding to the above target height range.

[0166] Optionally, the signal spectrum information can be calculated using the following formula (3).

[0167] S=f(n)(3)

[0168] Where S is the distance spectrum signal, n is any sampling point, n = 1, 2, ..., N, and f(n) is the function of power as a function of the frequency of n.

[0169] In this embodiment, the noise floor echo signal is analyzed using the radar parameter information of the UAV, which can yield accurate signal spectrum information.

[0170] The following describes the process of determining the spectrum calibration parameters based on the signal spectrum information in step S303 above.

[0171] Optionally, one possible approach to step S303 above includes:

[0172] Based on the above signal spectrum information and the preset polynomial fitting coefficients, polynomial fitting processing is performed to obtain the fitted polynomial; the coefficients in the fitted polynomial are used as the above spectrum calibration parameters.

[0173] Optionally, the number of coefficients in the above-fitted polynomial is the sum of the above-fitted polynomial coefficients and 1.

[0174] Optionally, the polynomial fitting coefficients mentioned above represent the number of coefficients in the fitted polynomial plus 1. For example, if the preset polynomial fitting coefficients are 1, then the number of coefficients in the fitted polynomial is 2. If the preset polynomial fitting coefficients are 2, then the number of coefficients in the fitted polynomial is 3.

[0175] Optionally, a pre-established fitting model can be used for polynomial fitting. Specifically, the aforementioned signal spectrum information and the aforementioned polynomial fitting coefficients are input into the target polynomial fitting model to obtain the aforementioned fitted polynomial.

[0176] For example, the target polynomial fitting model described above can be a polynomial fitting function, such as the polyfit function. The fitted polynomial can be obtained using the following formula (4).

[0177] P = polyfit(n, f(n), k)(4)

[0178] Where n is any sampling point, f(n) is the power corresponding to the frequency of sampling point n, and k is the polynomial fitting coefficient.

[0179] When k is 1, the fitted polynomial is a first-order linear function. When k is 2, the fitted polynomial is a second-order linear function, and so on.

[0180] When k is 1, assuming the fitted polynomial P is ax + b = 0, the coefficients in the fitted polynomial are [a, b], and the spectrum calibration parameters are [a, b].

[0181] When k is 2, assume the fitted polynomial P is ax 2 If +bx+c=0, then the coefficients in the fitted polynomial are [a,b,c], and the spectrum calibration parameters are [a,b,c].

[0182] In this embodiment, a preset polynomial fitting model can be used to achieve accurate polynomial fitting, thereby ensuring the accuracy of the coefficients in the fitted polynomial.

[0183] The process of generating the signal threshold curve based on the spectrum calibration parameters in step S304 above will be explained below.

[0184] Optionally, if the above calibration information is a signal threshold curve, then in step S304 above, a signal threshold curve corresponding to the target height range can be generated based on the above spectrum calibration parameters.

[0185] Figure 6 A flowchart illustrating the process of generating signal threshold curves corresponding to the target height range is shown below. Figure 6 As shown, the process includes:

[0186] S601. Based on the above spectrum calibration parameters and the frequency of each sampling point of the UAV's radar, generate the calibration curve corresponding to the above target altitude range.

[0187] Optionally, the calibration curve corresponding to the target height range can be obtained by fitting the above-mentioned spectrum calibration parameters and the frequency of each sampling point.

[0188] For example, the above calibration curve can be obtained by fitting and calculating using the following formula (5).

[0189] s c =h(n)=polyval(n,p) (5)

[0190] Where n is any sampling point, n = 1, 2, ..., N, p is the spectrum calibration parameter calculated by the aforementioned embodiment, and h(n) is the function of power as a function of the frequency of n.

[0191] S602. Based on the above calibration curve and the original threshold curve corresponding to the above target altitude range, the signal threshold curve corresponding to the above target altitude range is obtained. The original threshold curve is obtained based on the spectral analysis of the radar echo signal when the UAV is initially powered on.

[0192] Optionally, the calibration curve can be superimposed on the original threshold curve to obtain the signal threshold curve corresponding to the target height range.

[0193] The original threshold curve is generated when the drone is powered on and there is no interference. By superimposing the calibration curve corresponding to the background noise environment on it, the signal threshold curve corresponding to the target altitude range in the background noise environment can be obtained.

[0194] Assume the original threshold curve is as shown in the following formula (6).

[0195] th s = g(n), n = 1, 2, ..., N (6)

[0196] Where n is any sampling point, n = 1, 2, ..., N, and g(n) is a function of power as a function of the frequency of n.

[0197] The above signal threshold curve can be calculated using the following formula (7).

[0198] th sc = g(n) + h(n) (7)

[0199] Where g(n) is the original threshold curve and h(n) is the calibration curve mentioned above.

[0200] In the specific implementation process, when performing interference filtering through step S102 above, in the first method, interference filtering can be performed solely based on the aforementioned calibration information, and the specific process can be referred to the aforementioned embodiments. Alternatively, in the second method, interference filtering can also be performed by combining the aforementioned calibration information with other operating parameters of the UAV.

[0201] In the second method described above, interference filtering can be performed on the original echo signal collected by the UAV's radar based on the calibration information corresponding to the current altitude and the radar operating parameters corresponding to the current altitude, so as to obtain the filtered usable echo signal.

[0202] The radar operating parameters corresponding to the current altitude can include, for example, the blind zone range and / or signal-to-noise ratio (SNR) threshold. The blind zone range and SNR threshold can be determined in advance through simulation and other methods to ensure accurate blind zone ranges and SNR thresholds for different altitudes.

[0203] Therefore, in this embodiment, interference filtering can be performed simultaneously using the aforementioned calibration information, blind zone range, and signal-to-noise ratio (SNR) threshold. Specifically, the signals that need to be filtered can be determined separately using the aforementioned calibration information, blind zone range, and SNR threshold, and then the signals that need to be filtered can be determined comprehensively. For example, if a signal is determined to need filtering based on the calibration information, blind zone range, and SNR threshold, then that signal can be filtered. If a signal is determined to need filtering based on a portion of the calibration information, blind zone range, and SNR threshold, and not based on a portion of the criteria, then that signal can remain unfiltered. This combined filtering method further ensures the accuracy of interference filtering.

[0204] Based on the same inventive concept, this application also provides a radar signal processing device for a UAV corresponding to the radar signal processing method for a UAV. Since the principle of the device in this application is similar to the radar signal processing method for a UAV described above, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be described again.

[0205] Figure 7 A modular structure diagram of the radar signal processing device for a drone provided in this application embodiment is shown below. Figure 7 As shown, the device includes:

[0206] The acquisition module 701 is used to acquire the current altitude of the drone.

[0207] The filtering module 702 is used to perform interference filtering on the original echo signal collected by the radar of the UAV according to the calibration information corresponding to the current altitude, so as to obtain the filtered usable echo signal. The calibration information is used to characterize the echo signal characteristics of the radar in a preset noise floor environment.

[0208] As one possible implementation, the calibration information includes: a signal threshold curve, wherein the signal threshold curve is used to characterize the change in power of the radar echo signal with frequency in a preset noise floor environment;

[0209] The filtering module 702 is specifically used for:

[0210] The original echo signal is subjected to spectral analysis to obtain the actual spectrum information.

[0211] The actual spectrum information is compared with the signal threshold curve corresponding to the current height to determine the frequency to be filtered out, wherein the power of the frequency to be filtered out in the actual spectrum information is less than the power on the signal threshold curve.

[0212] The echo signals belonging to the frequency to be filtered out in the original echo signal are filtered out to obtain the usable echo signal.

[0213] As one possible implementation, the calibration information includes: spectrum calibration parameters.

[0214] The filtering module 702 is specifically used for:

[0215] Based on the spectral calibration parameters corresponding to the current height, the set original threshold curve is calibrated to obtain the signal threshold curve.

[0216] The original echo signal is subjected to interference filtering based on the signal threshold curve to obtain the usable echo signal.

[0217] As one possible implementation, the calibration information includes: spectrum calibration parameters.

[0218] The filtering module is specifically used for:

[0219] The original echo signal is calibrated according to the spectral calibration parameters corresponding to the current altitude to obtain the calibrated signal.

[0220] The calibrated signal is subjected to interference filtering by a set original threshold curve to obtain the usable echo signal.

[0221] As one possible implementation, the calibration information corresponding to different altitude ranges is obtained through pre-stored data. The filtering module 702 is also used for:

[0222] The noise floor echo signal collected by the radar of the UAV is obtained when the UAV is located in the noise floor environment and within the target altitude range.

[0223] Based on the noise floor echo signal, determine the signal spectrum information corresponding to the target height range.

[0224] Based on the signal spectrum information, determine the spectrum calibration parameters.

[0225] Based on the spectral calibration parameters, calibration information corresponding to the target height range is generated, and the calibration information corresponding to the target height range is used as the calibration information corresponding to each height within the target height range.

[0226] As one possible implementation, the filtering module 702 is specifically used for:

[0227] The number of sampling points is determined based on the pulse width and sampling period of the UAV's radar.

[0228] The frequency of each sampling point is determined based on the sampling frequency of the UAV's radar and the number of sampling points.

[0229] Spectral analysis was performed on the noise floor echo signal to obtain the power corresponding to the frequency of each sampling point.

[0230] Based on the frequency of each sampling point and the power corresponding to the frequency of each sampling point, the signal spectrum information corresponding to the target height range is obtained.

[0231] As one possible implementation, the filtering module 702 is specifically used for:

[0232] Based on the signal spectrum information and preset polynomial fitting coefficients, polynomial fitting processing is performed to obtain the fitted polynomial.

[0233] The coefficients in the fitted polynomial are used as the spectrum calibration parameters.

[0234] As one possible implementation, the filtering module 702 is specifically used for:

[0235] The signal spectrum information and the polynomial fitting coefficients are input into the target polynomial fitting model to obtain the fitted polynomial.

[0236] As one possible implementation, the filtering module 702 is specifically used for:

[0237] Based on the spectral calibration parameters, a signal threshold curve corresponding to the target height range is generated.

[0238] As one possible implementation, the filtering module 702 is specifically used for:

[0239] Based on the spectrum calibration parameters and the frequencies of each sampling point of the UAV's radar, a calibration curve corresponding to the target altitude range is generated.

[0240] Based on the calibration curve and the set original threshold curve corresponding to the target altitude range, the signal threshold curve corresponding to the target altitude range is obtained, wherein the original threshold curve is obtained based on the spectral analysis of the radar echo signal when the UAV is initially powered on.

[0241] As one possible implementation, the filtering module 702 is specifically used for:

[0242] Based on the spectral calibration parameters and the frequencies of each sampling point, a fitting process is performed to obtain the calibration curve corresponding to the target height range.

[0243] As one possible implementation, the filtering module 702 is specifically used for:

[0244] The calibration curve is superimposed on the original threshold curve to obtain the signal threshold curve corresponding to the target height range.

[0245] As one possible implementation, the filtering module 702 is specifically used for:

[0246] Based on the calibration information corresponding to the current altitude and the radar operating parameters corresponding to the current altitude, interference filtering is performed on the original echo signal collected by the UAV's radar to obtain the filtered usable echo signal.

[0247] The processing flow of each module in the device and the interaction flow between each module can be referred to the relevant descriptions in the above method embodiments, and will not be detailed here.

[0248] This application also provides an electronic device 800. Figure 8 This is a schematic diagram of the structure of an electronic device 800 provided in an embodiment of this application. The electronic device 800 may refer to the aforementioned drone or electronic device for controlling a drone. For example... Figure 8 As shown, the electronic device 800 includes a processor 801 and a memory 802. Optionally, it may also include a bus 803. The memory 802 stores machine-readable instructions executable by the processor 801. When the electronic device is running, the processor 801 and the memory 802 communicate via the bus 803. When the machine-readable instructions are executed by the processor 801, the method steps in the above method embodiments are performed.

[0249] This application also provides a computer-readable storage medium storing a computer program, which, when run by an electronic device, executes the steps of the radar signal processing method for the UAV described above.

[0250] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems and devices described above can be referred to the corresponding processes in the method embodiments, and will not be repeated here. In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed mutual coupling or direct coupling or communication connection can be through some communication interfaces; the indirect coupling or communication connection of devices or modules can be electrical, mechanical, or other forms.

[0251] 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. If the functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a 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 a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0252] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A radar signal processing method for an unmanned aerial vehicle (UAV), characterized in that, include: Obtain the drone's current altitude; Based on the calibration information corresponding to the current altitude, interference filtering is performed on the original echo signal collected by the radar of the UAV to obtain the filtered usable echo signal. The calibration information is used to characterize the radar echo signal characteristics in a preset low-noise environment. The calibration information corresponding to different altitude ranges is obtained through pre-stored data. The process of determining the calibration information corresponding to any altitude range includes: The noise floor echo signal collected by the radar of the UAV when the UAV is located in the noise floor environment and within the target altitude range; Based on the noise floor echo signal, determine the signal spectrum information corresponding to the target height range; Based on the signal spectrum information, determine the spectrum calibration parameters; Based on the spectral calibration parameters, calibration information corresponding to the target height range is generated, and the calibration information corresponding to the target height range is used as the calibration information corresponding to each height within the target height range.

2. The method according to claim 1, characterized in that, The calibration information includes a signal threshold curve, wherein the signal threshold curve is used to characterize the change in power of the radar echo signal with frequency in a preset noise floor environment. The step of performing interference filtering on the raw echo signal collected by the UAV's radar based on the calibration information corresponding to the current altitude to obtain a filtered usable echo signal includes: The original echo signal is subjected to spectral analysis to obtain the actual spectrum information; The actual spectrum information is compared with the signal threshold curve corresponding to the current height to determine the frequency to be filtered out, wherein the power of the frequency to be filtered out in the actual spectrum information is less than the power on the signal threshold curve; The echo signals belonging to the frequency to be filtered out in the original echo signal are filtered out to obtain the usable echo signal.

3. The method according to claim 1, characterized in that, The calibration information includes: spectrum calibration parameters; The step of performing interference filtering on the raw echo signal collected by the UAV's radar based on the calibration information corresponding to the current altitude to obtain a filtered usable echo signal includes: Based on the spectral calibration parameters corresponding to the current height, the set original threshold curve is calibrated to obtain the signal threshold curve; The original echo signal is subjected to interference filtering based on the signal threshold curve to obtain the usable echo signal.

4. The method according to claim 1, characterized in that, The calibration information includes: spectrum calibration parameters; The step of performing interference filtering on the raw echo signal collected by the UAV's radar based on the calibration information corresponding to the current altitude to obtain a filtered usable echo signal includes: The original echo signal is calibrated according to the spectral calibration parameters corresponding to the current altitude to obtain the calibrated signal; The calibrated signal is subjected to interference filtering by a set original threshold curve to obtain the usable echo signal.

5. The method according to claim 1, characterized in that, The step of determining the signal spectrum information corresponding to the target height range based on the background noise echo signal includes: The number of sampling points is determined based on the pulse width and sampling period of the UAV's radar. The frequency of each sampling point is determined based on the sampling frequency of the UAV's radar and the number of sampling points; Spectral analysis was performed on the noise floor echo signal to obtain the power corresponding to the frequency of each sampling point; Based on the frequency of each sampling point and the power corresponding to the frequency of each sampling point, the signal spectrum information corresponding to the target height range is obtained.

6. The method according to claim 1, characterized in that, The step of determining the spectrum calibration parameters based on the signal spectrum information includes: Based on the signal spectrum information and the preset polynomial fitting coefficients, polynomial fitting processing is performed to obtain the fitted polynomial. The coefficients in the fitted polynomial are used as the spectrum calibration parameters.

7. The method according to claim 6, characterized in that, The step of performing polynomial fitting processing based on the signal spectrum information and preset polynomial fitting coefficients to obtain a fitted polynomial includes: The signal spectrum information and the polynomial fitting coefficients are input into the target polynomial fitting model to obtain the fitted polynomial.

8. The method according to claim 1, characterized in that, The step of generating calibration information corresponding to the target altitude range based on the spectral calibration parameters includes: Based on the spectral calibration parameters, a signal threshold curve corresponding to the target height range is generated.

9. The method according to claim 8, characterized in that, The step of generating the signal threshold curve corresponding to the target height range based on the spectrum calibration parameters includes: Based on the spectrum calibration parameters and the frequencies of each sampling point of the UAV's radar, a calibration curve corresponding to the target altitude range is generated; Based on the calibration curve and the set original threshold curve corresponding to the target altitude range, the signal threshold curve corresponding to the target altitude range is obtained, wherein the original threshold curve is obtained based on the spectral analysis of the radar echo signal when the UAV is initially powered on.

10. The method according to claim 9, characterized in that, The step of generating a calibration curve corresponding to the target altitude range based on the spectrum calibration parameters and the frequencies of each sampling point of the UAV's radar includes: Based on the spectral calibration parameters and the frequencies of each sampling point, a fitting process is performed to obtain the calibration curve corresponding to the target height range.

11. The method according to claim 9, characterized in that, The step of obtaining the signal threshold curve corresponding to the target height range based on the calibration curve and the set original threshold curve corresponding to the target height range includes: The calibration curve is superimposed on the original threshold curve to obtain the signal threshold curve corresponding to the target height range.

12. The method according to any one of claims 1-11, characterized in that, The step of performing interference filtering on the raw echo signal collected by the UAV's radar based on the calibration information corresponding to the current altitude to obtain a filtered usable echo signal includes: Based on the calibration information corresponding to the current altitude and the radar operating parameters corresponding to the current altitude, interference filtering is performed on the original echo signal collected by the UAV's radar to obtain the filtered usable echo signal.

13. A radar signal processing device for an unmanned aerial vehicle (UAV), characterized in that, include: The acquisition module is used to obtain the current altitude of the drone; The filtering module is used to perform interference filtering on the original echo signal collected by the radar of the UAV according to the calibration information corresponding to the current altitude, so as to obtain the filtered usable echo signal. The calibration information is used to characterize the features of the usable echo signal of the radar in a preset noise floor environment. The calibration information corresponding to different altitude ranges is obtained through pre-stored data. The process of determining the calibration information corresponding to any altitude range includes: The noise floor echo signal collected by the radar of the UAV when the UAV is located in the noise floor environment and within the target altitude range; Based on the noise floor echo signal, determine the signal spectrum information corresponding to the target height range; Based on the signal spectrum information, determine the spectrum calibration parameters; Based on the spectral calibration parameters, calibration information corresponding to the target height range is generated, and the calibration information corresponding to the target height range is used as the calibration information corresponding to each height within the target height range.

14. An electronic device, characterized in that, include: The processor and memory, the memory storing machine-readable instructions executable by the processor, wherein when the electronic device is running, the processor executes the machine-readable instructions to perform the steps of the radar signal processing method for the UAV as described in any one of claims 1 to 12.

15. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, performs the steps of the radar signal processing method for the UAV as described in any one of claims 1 to 12.

Images