Radar signal processing method and agricultural unmanned aerial vehicle

Abstract

The invention provides a radar signal processing method and an agricultural unmanned aerial vehicle, different links of radar signal processing can be configured with special storage spaces, and each processing link can continue to process data of a next stage after completing data processing of a previous stage. The radar signal is not blocked due to the influence of the processing result of the data in the previous stage, and the processing efficiency of the radar signal is high. Besides, the DOA estimation link can be processed by using a distance fast Fourier transform result, angle information in a radar signal processing result is not influenced by Doppler frequency shift, and the calculation precision of a horizontal angle and / or a vertical angle is higher. The agricultural unmanned aerial vehicle using the method is high in radar data processing efficiency, good in operation quality and high in operation safety.

Description

Technical Field

[0001] The present application relates to the technical field of radar signal processing, and in particular, to a radar signal processing method and an agricultural drone. Background Art

[0002] In agricultural production, agricultural drones can be used for sowing, spraying pesticides or fertilizers, or detecting pests and diseases. In the above operations, agricultural drones equipped with radars have higher environmental perception capabilities and more precise operation capabilities. During the operation, agricultural drones need to continuously send radar signals, receive radar signals, process radar signals, and respond based on the processing results of radar signals.

[0003] The angle information in the processing results of radar signals will affect the working quality of agricultural drones, and in some cases may also affect the safety and life of agricultural drones. How to improve the accuracy of output angle information while improving the processing efficiency of agricultural drones for radar signals is a problem worth considering. Summary of the invention

[0004] The present application provides a radar signal processing method and an agricultural drone. Different processing links of the radar signal can process different radar data in parallel, and the calculation of angle information is not affected by Doppler frequency shift. The radar signal processing efficiency of the agricultural drone using the signal processing method is high and the angle information is more accurate.

[0005] In a first aspect, a method for radar signal processing is provided, which is applied to a radar device. The radar device includes a first processing module, a second processing module, a third processing module, a first storage module, a second storage module and a third storage module. The method includes: the first processing module processes first data and stores second data in the first storage module, and the second data is a processing result of the first data; the second processing module processes second data and stores third data in the second storage module, and the third data is a first processing result of the second data; the third processing module processes second data and stores fourth data in the third storage module, and the fourth data is a second processing result of the second data; wherein the first processing module is used to perform range fast Fourier transform processing, the second processing module is used to perform Doppler fast Fourier transform processing, and the third processing module is used to perform arrival direction estimation processing.

[0006] In the technical solution, the first processing module, the second processing module, and the third processing module are all configured with dedicated storage space. After completing the processing of the first data (data of the current batch of radar signals), the first processing module can continue to process the next batch of radar signals. The first processing module has high efficiency in processing data. Similarly, the second processing module and the third processing module have high processing efficiency. The radar device processes radar signals more efficiently and consumes less energy. In addition, the data for performing the direction of arrival estimation processing is the data after the range Fourier transform, which has not undergone the Doppler Fourier transform and is not affected by the Doppler frequency shift. The accuracy of the angle information obtained by the direction of arrival estimation processing is higher.

[0007] In combination with the first aspect, in certain implementations of the first aspect, the size of the first storage module is determined according to the number of sampling points, the number of transmitting antennas, the number of receiving antennas, and the number of chirp signals; the size of the second storage module is determined according to the number of sampling points, the number of transmitting antennas, the number of receiving antennas, and the number of chirp signals.

[0008] In the technical solution, the size of the first storage module and the size of the second storage module can be determined according to data such as the number of sampling points, and the storage resources of the radar device are efficiently utilized.

[0009] In combination with the first aspect, in certain implementations of the first aspect, the size of the third storage module is determined according to the maximum output target number of the radar signal and the angular accuracy of the radar device.

[0010] In the technical solution, the size of the storage space configured in different links of radar signal processing can be configured according to the amount of data to be processed, and the storage resources of the radar device are efficiently utilized.

[0011] In combination with the first aspect, in certain implementations of the first aspect, the size of the third storage module is also determined according to a working scenario of the radar device.

[0012] In combination with the first aspect, in certain implementations of the first aspect, the working scene includes a first target scene and a second target scene, the first target scene satisfies one or more of the following: the terrain is flat, the height difference of crops is less than or equal to the height threshold, or the planting density of crops is less than or equal to the density threshold; the second target scene satisfies one or more of the following: the terrain is undulating, the height difference of crops is greater than the height threshold, or the planting density of crops is greater than the density threshold; the size of the third storage module corresponding to the first target scene is smaller than the size of the third storage module corresponding to the second target scene.

[0013] In a possible implementation, the third storage module corresponding to the second target scene may include a first sub-storage module and a second sub-storage module, the first sub-storage module may be used to store horizontal angle data, and the second sub-storage module may be used to store vertical angle data. The third storage module corresponding to the first target scene may include the aforementioned first sub-storage module, which is used to store horizontal angle data.

[0014] In this technical solution, the size of the storage module in the wave direction estimation processing link can be determined according to the working scene of the radar device. In the scene where the vertical angle is more important, a larger space can be configured for the aforementioned storage module, and in the scene where the vertical angle has little effect on the operation of the agricultural drone, a smaller space can be configured for the aforementioned storage module. The implementation of this technical solution is conducive to improving the utilization efficiency of the storage resources of the radar device.

[0015] In combination with the first aspect, in certain implementations of the first aspect, the radar device also includes a fourth processing module, a fifth processing module, a fourth storage module and a fifth storage module, and the method also includes: the fourth processing module processes the third data, and stores the fifth data in the fourth storage module, and the fifth data is the processing result of the third data; the fifth processing module processes the fifth data, and stores the sixth data in the fifth storage module, and the sixth data is the processing result of the fifth data; wherein the fourth processing module is used to perform incoherent combination processing, and the fifth processing module is used to perform constant virtual warning processing.

[0016] In combination with the first aspect, in some implementations of the first aspect, the size of the fourth storage module is determined according to the number of sampling points and the number of chirp signals, and the size of the fifth storage module is determined according to the number of sampling points.

[0017] In combination with the first aspect, in some implementations of the first aspect, the first processing module has read and write permissions to the first storage module, the second processing module has read permissions to the first storage module, and the third processing module has read permissions to the first storage module.

[0018] The radar device can configure storage spaces of different sizes for different links of radar signal processing according to the actual working scenario, and the storage resources of the radar device are efficiently utilized.

[0019] In a second aspect, an agricultural UAV is provided, comprising a power device, a radar device and an operating device, wherein the power device is used to provide power for the agricultural UAV, the operating device is used to perform agricultural operations, and the radar device is used to implement the method in the first aspect and any possible implementation thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 This is an application scenario of an agricultural drone provided in an embodiment of the present application.

[0021] Figure 2 This is another application scenario of an agricultural drone provided in an embodiment of the present application.

[0022] Figure 3 It is a schematic diagram of the hardware architecture of a radar device provided in an embodiment of the present application.

[0023] Figure 4 It is a schematic diagram of a radar signal processing method provided in an embodiment of the present application.

[0024] Figure 5 It is a schematic diagram of another radar signal processing method provided in an embodiment of the present application.

[0025] Figure 6 It is a schematic diagram of another radar signal processing method provided in an embodiment of the present application.

[0026] Figure 7 It is a schematic diagram of an agricultural drone provided in an embodiment of the present application. DETAILED DESCRIPTION

[0027] The terms used in the following embodiments are only for the purpose of describing specific embodiments, and are not intended to be used as limitations on the present application. As used in the specification and the appended claims of the present application, the singular expressions "one", "a kind of", "above", "the" and "this" are intended to also include expressions such as "one or more", unless there is a clear contrary indication in the context. It should also be understood that in the following embodiments of the present application, "at least one", "one or more" refer to one, two or more. The term "and / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist; for example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship.

[0028] References to "one embodiment" or "some embodiments" etc. described in this specification mean that a particular feature, structure or characteristic described in conjunction with the embodiment is included in one or more embodiments of the present application. Thus, the phrases "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear at different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0029] Embodiments of the present application are described in detail below, and examples of the embodiments of the present application are shown in the accompanying drawings. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application, and cannot be understood as limiting the present application.

[0030] In order to make the technical problems solved by the present application, the technical solutions adopted and the technical effects achieved more clear, the technical solutions of the embodiments of the present application will be further described in detail below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments.

[0031] Agricultural drones are also called agricultural drones, plant protection drones or plant protection machines. During operation, agricultural drones can determine the distance, speed, horizontal angle or vertical angle of the target by sending radar signals and receiving radar echoes reflected from objects, and then perform corresponding operations. Generally, different operation scenarios have different performance requirements for the radar device of agricultural drones, and the corresponding power consumption of radar devices with different performance also varies.

[0032] Figure 1 The figure shows a working scene 10 of the agricultural drone 100. In this working scene 10, the agricultural drone 100 is basically in a parallel flight operation state. In other words, in this working scene 10, the agricultural drone 100 may encounter fewer situations where it needs to adjust the flight altitude.

[0033] For example, in the working scene 10, crops can be planted in a relatively flat farmland. For example, in the working scene 10, the heights of the crops can be substantially the same, or the difference in the heights of the crops is less than the height threshold. For example, in the working scene 10, the agricultural drone 100 can be in a low-altitude flight state. For example, in the working scene 10, the agricultural drone 100 can be used to spray pesticides on cotton in plain areas.

[0034] In the above working scenario 10, the agricultural drone 100 can perform basic obstacle avoidance, roughly adjust the flight altitude, etc. according to the radar signal. In this scenario, the agricultural drone 100 does not have high requirements for the performance of the radar signal, for example, the agricultural drone 100 does not have high requirements for the height measurement accuracy of the radar signal.

[0035] Figure 2 Another working scenario 20 of the agricultural drone 100 is shown. In this working scenario 20, the agricultural drone 100 needs to frequently adjust the flight altitude to adapt to the working scenario.

[0036] Exemplarily, the obstacles included in the working scene 20 are relatively dense, or in other words, the agricultural drone 100 in the working scene 20 is in an environment with dense obstacles. Exemplarily, the crops in the working scene 20 can be planted in a mountainous area, a basin or a hilly area with undulating terrain. Exemplarily, there may be obvious differences in the height of the crops in the working scene 20, or in other words, the height difference of the crops in the working scene 20 is greater than the height threshold. For example, in the working scene 20, the agricultural drone 100 can be used to inspect pests and diseases for fruit trees in hilly areas.

[0037] In the working scenario 20, the agricultural drone 100 may need to accurately and frequently adjust the flight altitude, flight attitude, etc. In this working scenario 20, the agricultural drone 100 has high performance requirements for the radar device. For example, the agricultural drone 100 has high requirements for the measurement accuracy of the height and distance of obstacles, and high requirements for the processing efficiency of radar signals.

[0038] Figure 3 The schematic diagram of the hardware architecture of a radar device 200 provided in an embodiment of the present application is shown. As shown in the figure, the radar device 200 may include a processing module 210, a radio frequency front-end module 220, a power management module 230 and an internal memory 240.

[0039] In some examples, the radar device 200 may include multiple RF front-end modules 220, or the number of RF front-end modules 220 may be multiple, for example, RF front-end module 220-1, RF front-end module 220-2, RF front-end module 220-3 and RF front-end module 220-N (N is an integer greater than or equal to 2). The RF front-end module 220 may include a transmitting antenna, a receiving antenna, a signal generator, a power amplifier or a low noise amplifier (LNA), etc. Among them, the transmitting antenna can be used to transmit radar signals, and the receiving antenna can be used to receive radar echo signals; the signal generator can be used to generate a transmission signal with a predetermined frequency and modulation characteristics; the power amplifier can be used to amplify the signal generated by the signal generator to a sufficient power level so as to be effectively transmitted; the low noise amplifier can be used to preliminarily amplify the received weak signal while maintaining a low noise coefficient.

[0040] In some examples, the processing module 210 can be used to process and analyze the signal received by the radar device. Exemplarily, the processing module 210 can include an analog-to-digital converter (ADC), which can be used to convert the analog signal received by the radar device 200 into a digital signal. Exemplarily, the processing module 210 can include a digital signal processor (DSP), which can be used to process the digital signal, for example, perform fast Fourier transform (FFT), Doppler filtering or target detection on the digital signal.

[0041] Exemplarily, the processing module 210 may also include one or more of a microcontroller unit (MCU), a system on chip (SOC), or a field programmable gate array (FPGA).

[0042] In some examples, the power management module 230 can be used to manage and control the power supply of the electronic components included in the radar device 200, so that each electronic component can obtain a stable, efficient and reliable power supply. Exemplarily, the power management module 230 can be used to implement one or more of the following functions: voltage conversion, current regulation, power monitoring or energy saving management, etc.

[0043] In some examples, the internal memory 240 may be used to store executable program codes used in the signal or data processing process performed by the aforementioned processing module 210, and the executable program codes may include instructions. The processing module 210 may implement the processing of the radar signal by running the instructions stored in the internal memory 240. Exemplarily, the internal memory 240 may include a high-speed random access memory, and may also include a non-volatile memory (e.g., a flash memory device), etc.

[0044] In some examples, the radar device 200 may further include one or more interfaces 250, which may be used for data exchange between the radar device 200 and other devices or equipment. Exemplarily, the interface 250 may be one or more of a controller area network flexible data-rate (CAN FD) interface, an Ethernet physical layer (ENET PHY) interface, or a quadrature serial peripheral interface (QSPI).

[0045] It should be noted that the above only provides some electronic components or functional modules that the radar device 200 may include by way of example. The radar device 200 may also include more or fewer electronic components or functional modules, and this application does not impose any limitation on this.

[0046] In the process of processing radar echo signals, the signal needs to be processed in multiple links, and the processing result of the data in the previous link needs to be used in the next link.

[0047] like Figure 4 As shown, during the processing of the radar echo signal, the agricultural drone 100 can perform analog-to-digital conversion, range fast Fourier transform, Doppler fast Fourier transform and other operations on the signal in sequence after receiving the radar echo signal. The specific processing flow is roughly as follows.

[0048] S101, analog-to-digital conversion.

[0049] The RF front-end module 220 of the radar device 200 can receive the radar echo signal and input the radar echo signal to the analog-to-digital converter, which can convert the radar echo signal into a digital signal for subsequent processing.

[0050] S102, range fast Fourier transform (range FFT).

[0051] Typically, the electromagnetic wave signal emitted by the radar device 200 is a chirp signal whose frequency increases or decreases linearly with time. When this signal encounters a target and is reflected back to the radar device 200, due to the round-trip propagation time of the signal, the radar echo signal will have a frequency difference with the currently emitted signal, and this frequency difference is directly related to the distance of the target. The distance fast Fourier transform can be used to separate the distance information of each target from the received mixed signal.

[0052] The distance fast Fourier transform can convert the time domain signal into the frequency domain signal, so that the radar echo signal at different distances appears as different peaks on the spectrum, and the position of each peak corresponds to a specific distance. By analyzing the results of the distance fast Fourier transform, combined with the radar's operating frequency, the slope of the chirp signal, the sampling rate, and the speed of light, the distance corresponding to each peak can be calculated. The following formula roughly gives the relationship between the target distance and the frequency:

[0053]

[0054] Among them, R represents the distance of the target, c represents the speed of light, f represents the operating frequency of the radar, and k represents the frequency index.

[0055] In some examples, radar device 200 may directly use the processing result of the range fast Fourier transform to estimate the direction of arrival, which is helpful to reduce the adverse effect of Doppler frequency shift on the accuracy of angle calculation in the result of radar signal processing to a certain extent.

[0056] S103, Doppler fast Fourier transform (Doppler FFT).

[0057] In order to extract velocity information from a target at a specific distance, the echo information of multiple continuous chirp signals can be processed by Doppler fast Fourier transform, for example, by accumulating the data of the echo signals of all chirp signals within the same distance range and performing fast Fourier transform on the accumulated data.

[0058] Due to the relative motion between the target and the radar device 200, this relative motion will produce additional frequency shift within a specific distance range. The result of Doppler fast Fourier transform is a frequency-Doppler spectrum, and the peak position on the spectrum can reflect the speed of the target.

[0059] S104, Non-coherent Combining (NCC).

[0060] Also known as incoherent combining, it is used to integrate the signal energy of different channels in the radar signal processing process to improve the signal-to-noise ratio of target detection.

[0061] Typically, during the incoherent combination process, the amplitudes of signals from different receiving paths (e.g., antennas) may be processed. Specifically, a modulo operation may be performed on the complex signal of each receiving channel to convert it into amplitude information of the signal. The signal energy after noise suppression may be obtained by accumulating the amplitude information of all channels and averaging the accumulated amplitude signals.

[0062] S105, constant false alarm.

[0063] Constant false alarm rate (CFAR) is used to detect objects in a noisy background. By dynamically adjusting the detection threshold, the false alarm rate remains constant under different environmental conditions.

[0064] S106, direction of arrival (DOA) estimation.

[0065] Direction of arrival estimation is used to determine the angle information of the target based on the radar echo signal, which can include the horizontal angle (azimuth) and the vertical angle (pitch angle).

[0066] Exemplarily, the direction of arrival estimation can be performed by one or more of the following algorithms: fast Fourier transform and delay-and-sum beamforming (DBF), multiple signal classification (MUSIC) and estimation of signal parameters via rotational invariance techniques (ESPRIT), orthogonal matching pursuit (OMP) or reduced-dimension atomic norm minimization (RD-ANM) algorithm, etc.

[0067] In some examples, the radar device 200 may use the processing result of the constant false warning to perform direction of arrival estimation.

[0068] Usually, Doppler Fast Fourier Transform can use the change of phase difference between adjacent chirp signals to estimate the speed of the target, and the Doppler frequency shift of the target is not considered in this process.

[0069] When using the processing results of constant false alarm to estimate the direction of arrival, since the input data of the constant false alarm has undergone a Doppler fast Fourier transform, in other words, the result of the Doppler fast Fourier transform is used for calculation in the process of the direction of arrival estimation, the aforementioned Doppler frequency shift will cause inaccurate calculation results of the direction of arrival estimation to a certain extent, or, in other words, will cause inaccurate angle measurement in the results of radar signal processing.

[0070] Taking a 3-transmit 4-receive time division multiplexing-multiple input multiple output antenna as an example, due to the Doppler effect caused by target motion, the four virtual antennas formed by transmit antenna 2 and transmit antenna 3 will produce Doppler phase shift relative to the four virtual antennas formed by transmit antenna 1. The phase difference caused by this Doppler frequency shift will be mapped to the angle, resulting in inaccurate angle measurement.

[0071] In some examples, when using the processing result of the constant false warning to perform wave direction estimation, phase offset correction, or Doppler phase compensation, can be performed before performing the wave direction estimation process, which can reduce the angle error caused by the Doppler frequency shift to a certain extent.

[0072] In order to reduce the adverse effect of Doppler frequency shift on angle measurement in DOA estimation, in some examples, radar device 200 may use range fast Fourier transform to perform DOA estimation. In this case, the data used for DOA estimation is not subjected to Doppler fast Fourier transform, and the inaccuracy of angle measurement caused by Doppler frequency shift will not be caused.

[0073] like Figure 5 Another radar signal processing method provided in an embodiment of the present application is shown. The agricultural UAV can adopt different wave direction estimation methods according to different working scenarios, thereby reducing the power consumption of the radar device 200 to a certain extent.

[0074] S201, determine the working scenario.

[0075] In some examples, the agricultural drone may include a radar device, through which the agricultural drone may send out a transmission signal and receive a radar echo signal, and a working scene may be determined according to the processing result of the radar echo signal.

[0076] For example, the agricultural drone can identify the terrain of the working scene based on the received radar echo data, such as the ups and downs of the field, the location of obstacles, etc. One possible situation is that the agricultural drone determines that the terrain in the working scene is relatively flat based on the radar echo data. For example, the working scene can be Figure 1 One possible scenario is that the agricultural drone determines based on radar echo data that the terrain in the working scene varies greatly. For example, the working scene can be Figure 2 The scene shown.

[0077] Exemplarily, the agricultural drone can determine the height of crops and / or the density of crops based on the received radar echo data. One possible scenario is that the agricultural drone determines that the height of crops in the working scene is basically consistent and / or the density of crops (or planting density) is relatively sparse based on the radar echo data, or that the difference in the height of crops in the working scene determined by the agricultural drone based on the radar echo data is less than or equal to the height threshold, and / or the density of crops is less than or equal to the density threshold. One possible scenario is that the agricultural drone determines that the height difference of crops in the working scene is large and / or the density of crops is relatively dense based on the radar echo data, or that the difference in the height of crops in the working scene determined by the agricultural drone based on the radar echo data is greater than the height threshold, and / or the density of crops is greater than the density threshold.

[0078] In some examples, the agricultural drone may include a visual sensor such as a camera, and the agricultural drone may obtain image information of the working scene through the visual sensor, and the working scene may be determined based on the image information.

[0079] For example, the agricultural drone acquires a high-resolution image of the working scene through an image sensor, and the coverage of crops or the planting density of crops in the working scene can be determined based on the image. One possible scenario is that the planting density of crops in the working scene is relatively sparse. Another possible scenario is that the planting density of crops in the working scene is relatively dense.

[0080] Exemplarily, the agricultural drone acquires a high-resolution image of the working scene through an image sensor, and the pest and disease situation of the crops in the working scene can be determined based on the image. One possible situation is that the pest and disease of the crops in the working scene is relatively serious, for example, the crops with pest and disease in the working scene are widely distributed, or there are many parts of the crops with pest and disease in the working scene. One possible situation is that the pest and disease of the crops in the working scene is relatively minor, for example, the crops with pest and disease in the working scene are concentratedly distributed, or there are few parts of the crops with pest and disease in the working scene.

[0081] In some examples, the working scene may include a first target scene and a second target scene, wherein the first target scene may satisfy one or more of the following: the terrain is relatively flat, the height of crops is basically consistent, the planting density of crops is relatively sparse, or the crop diseases and insect pests are relatively mild; the second target scene may satisfy one or more of the following: the terrain is undulating, the height of crops is quite different, the planting density of crops is relatively dense, or the crop diseases and insect pests are relatively serious.

[0082] In some examples, the work scene may also include a third target scene, which may include one or more of the following: precision work, crop monitoring, low-altitude flight, or terrain following.

[0083] For example, the above-mentioned precision operation may include precision spraying operation, for example, agricultural drones perform spraying of pesticides, fertilizers or other chemicals. In this working scenario, agricultural drones need to maintain a relatively stable flight altitude and attitude, and slight changes in the vertical angle will affect the uniformity of spraying, which may result in insufficient or excessive spraying in certain areas, thereby affecting the growth and health of crops.

[0084] For example, the crop monitoring mentioned above may refer to the monitoring of crop health by agricultural drones. In this working scenario, agricultural drones need to maintain a relatively stable flight attitude to obtain high-quality images or spectral data. Slight changes in the vertical angle will cause blurred images taken by agricultural drones or inaccurate detected data, thus affecting the analysis results.

[0085] S202: Determine a direction of arrival estimation method according to a working scenario.

[0086] In some examples, when the agricultural drone is in the aforementioned first target scene, the calculation result of the pitch angle has little or no effect on the operation of the agricultural drone. In this case, in the wave direction estimation processing link, the agricultural drone can only calculate the horizontal angle.

[0087] In some examples, when the agricultural UAV is in the aforementioned second target scene, the calculation result of the pitch angle has a certain impact on the operation of the agricultural UAV. In this case, in the wave direction estimation processing link, the agricultural UAV can use the processing result of the Hengxu warning to estimate the wave direction.

[0088] In some examples, when the agricultural drone is in the aforementioned third target scenario, a small error in the calculation result of the pitch angle may affect the quality of the agricultural drone's work, and may even affect the safety and service life of the agricultural drone. In this case, in order to improve the processing accuracy of the direction of arrival processing link for the angle information of the target, the agricultural drone can directly use the processing result of the distance fast Fourier transform to estimate the direction of arrival.

[0089] S203, output radar data detection results.

[0090] Agricultural drones can be used according to the Figure 1 The related description processes the radar data to determine information such as the direction, distance, speed, and angle of the target, thereby outputting the detection results of the radar data.

[0091] like Figure 6Another radar signal processing method provided by an embodiment of the present application is shown. Different links of radar signal processing can be allocated dedicated storage space. In the data processing flow, the later processing link will not block the earlier processing link, and the radar signal processing efficiency is high.

[0092] S301 - 1 , the processing module A performs a first processing on the sampled data A to generate data A1 .

[0093] Here, the processing module A can be used to perform a range fast Fourier transform on the sampled data A, the first processing can be regarded as a range fast Fourier transform, and the data A1 can be regarded as a processing result of the range fast Fourier transform.

[0094] The processing module A corresponds to the storage module A, or in other words, the first processing corresponds to the storage module A. The result (data A1) of the first processing of the sample data A by the processing module A can be stored in the storage module A.

[0095] In some examples, processing module A has write permission and read permission on the storage space of storage module A.

[0096] In some examples, after completing the first processing of sampled data A, processing module A may continue to perform the first processing on sampled data B and generate data B1. When processing module B reads data A1 from storage module A, data B1 may be stored in storage module A for processing module B to read.

[0097] Similarly, after completing the first processing of the sampled data B, the processing module A can continue to perform the first processing on the sampled data C (for example, executing the operation of S301-2) and generate data C1. In the case where the processing module B reads the data B1 from the storage module A, the data C1 can be stored in the storage module A for the processing module B to read.

[0098] In order to improve the utilization efficiency of the storage resources of the radar device, in some examples, the size of the storage space of the storage module A can be determined according to the amount of sampled data. For example, the storage space Ma of the storage module A can be calculated according to the following formula:

[0099] Ma=2×S×N Tx ×N Rx ×N chirp (1)

[0100] Where S represents the number of sampling points, N Tx Represents the number of transmitting antennas of the radar device, N Rx Represents the number of receiving antennas of the radar device, N chirp Indicates the number of chirp signals or the number of complete transmit and receive cycles.

[0101] S302a, processing module B performs a second process on data A1 to generate data A2.

[0102] The processing module B may read the data A1 from the storage module A and perform a second process on the data A1.

[0103] Here, the processing module B can be used to perform Doppler fast Fourier transform on the data A1, the second processing can be regarded as Doppler fast Fourier transform, and the data A2 can be regarded as the processing result of Doppler fast Fourier transform.

[0104] The processing module B corresponds to the storage module B, or in other words, the second processing corresponds to the storage module B. The result (data A2) of the second processing performed by the processing module B on the data A1 can be stored in the storage module B.

[0105] In some examples, processing module B has write permission and read permission on the storage space of storage module B.

[0106] In some examples, processing module B has read permission on the storage space of storage module A.

[0107] In some examples, after completing the second processing of data A1, processing module B may continue to perform the second processing on data B1 and generate data B2. When processing module C reads data A2 from storage module B, data B2 may be stored in storage module B for processing module C to read.

[0108] Similarly, after completing the second processing on data B1, processing module B may continue to perform the second processing on data C1 and generate data C2. When processing module C reads data B2 from storage module B, data C2 may be stored in storage module B for processing module C to read.

[0109] In order to improve the utilization efficiency of the storage resources of the radar device, in some examples, the size of the storage space of the storage module B can be determined according to the amount of sampled data. Exemplarily, the storage space Mb of the storage module B can be calculated according to the following formula:

[0110] Mb=2×S×N Tx ×N Rx ×N chirp (2)

[0111] Where S represents the number of sampling points, N Tx Represents the number of transmitting antennas of the radar device, N Rx Represents the number of receiving antennas of the radar device, N chirp Indicates the number of chirp signals or the number of complete transmit and receive cycles.

[0112] S302b, the processing module E performs the fifth processing on the data A1 to generate data A5.

[0113] The processing module E may read the data A1 from the storage module A and perform the fifth processing on the data A1.

[0114] Here, the processing module E can be used to perform direction of arrival estimation on the data A1, the fifth process can be regarded as a direction of arrival estimation process, and the data A1 can be regarded as a result of the direction of arrival estimation process.

[0115] The processing module E corresponds to the storage module E, or in other words, the fifth process corresponds to the storage module E. The result (data A5) of the fifth process performed by the processing module E on the data A1 can be stored in the storage module E.

[0116] In some examples, processing module E has write permission and read permission on the storage space of storage module E.

[0117] In some examples, processing module E has read permission on the storage space of storage module A.

[0118] In some scenarios, the result (data A5) of the fifth processing performed by the processing module E on the data A1 may include the vertical angle and the horizontal angle of the target.

[0119] In order to improve the utilization efficiency of the storage resources of the radar device, in some examples, the size of the storage space of the storage module E can be determined according to the amount of sampled data. Exemplarily, the storage space Me of the storage module E can be calculated according to the following formula:

[0120] Me=N target ×4×N rs (5)

[0121] Among them, N target Indicates the maximum number of output targets, N rs Indicates the number of beams corresponding to the field of view of the radar device. For the calculation of the horizontal angle, N rs It can refer to the number of beams that can be formed in the horizontal direction by the field of view of the radar device; for the calculation of the vertical angle, N rs It may refer to the number of beams that can be formed in the vertical direction by the field of view of the radar device. In some examples, the number of beams is related to the field of view of the radar device and the angular accuracy of the radar device.

[0122] One possible situation is that the agricultural drone is in the first target scene. In step S302b, only the information of the horizontal angle may be stored without storing the information of the vertical angle. In this case, the storage space of the storage module E may be smaller.

[0123] One possible situation is that the agricultural drone is in the second target scene. In step S302b, the horizontal angle information and the vertical angle information can be stored simultaneously. In this case, the storage space of the storage module E can be larger.

[0124] As an example but not limitation, the storage module E corresponding to the second target scene may include a first sub-storage module and a second sub-storage module, the first sub-storage module may be used to store horizontal angle data, and the second sub-storage module may be used to store vertical angle data. The storage module E corresponding to the first target scene may include the aforementioned first sub-storage module for storing horizontal angle data.

[0125] In some examples, after completing the fifth processing on the sampled data A1, the processing module E may continue to perform the fifth processing on the data B1 to generate data B5, and store the data B5 in the storage module E. Similarly, after completing the fifth processing on the data B1, the processing module E may continue to perform the fifth processing on the data C1 to generate data C5, and store the data C5 in the storage module E.

[0126] S303, the processing module C performs a third process on the data A2 to generate data A3.

[0127] The processing module C can read the data A2 from the storage module B and perform a third process on the data A2.

[0128] Here, the processing module C can be used to perform incoherent combination on the data A2, the third process can be regarded as the incoherent combination process, and the data A3 can be regarded as the result of the incoherent combination process.

[0129] The processing module C corresponds to the storage module C, or in other words, the third processing corresponds to the storage module C. The result (data A3) of the third processing performed by the processing module C on the data A2 can be stored in the storage module C.

[0130] In some examples, processing module C has write permission and read permission on the storage space of storage module C.

[0131] In some examples, processing module C has read permission on the storage space of storage module B.

[0132] In some examples, after completing the third processing on data A2, processing module C may continue to perform the third processing on data B2 and generate data B3. When processing module D reads data A3 from storage module C, data B3 may be stored in storage module C for processing module D to read.

[0133] Similarly, after completing the third processing on data B2, processing module C can continue to perform the third processing on data C2 and generate data C3. When processing module D reads data B3 from storage module C, data C3 can be stored in storage module C for processing module D to read.

[0134] In order to improve the utilization efficiency of the storage resources of the radar device, in some examples, the size of the storage space of the storage module C can be determined according to the amount of sampled data. Exemplarily, the storage space Mc of the storage module C can be calculated according to the following formula:

[0135] Mc=2×S×N chirp (3)

[0136] Where S represents the number of sampling points, N chirp Indicates the number of chirp signals or the number of complete transmit and receive cycles.

[0137] S304, the processing module D performs a fourth process on the data A3 to generate data A4.

[0138] The processing module D may read the data A3 from the storage module C and perform the fourth processing on the data A3.

[0139] Here, the processing module D can be used to perform constant virtual warning processing on the data A3, the fourth processing can be regarded as the constant virtual warning processing, and the data A4 can be regarded as the processing result of the constant virtual warning.

[0140] The processing module D corresponds to the storage module D, or in other words, the fourth processing corresponds to the storage module D. The result (data A4) of the fourth processing performed by the processing module D on the data A3 can be stored in the storage module D.

[0141] In some examples, processing module D has write permission and read permission on the storage space of storage module D.

[0142] In some examples, processing module D has read permission on the storage space of storage module C.

[0143] In some examples, after completing the fourth processing on data A3, processing module D may continue to perform the fourth processing on data B3 and generate data B4. When processing module E reads data A4 from storage module D, data B4 may be stored in storage module D and may be read by processing module E.

[0144] Similarly, after completing the fourth processing on data B3, processing module D may continue to perform the fourth processing on data C3 and generate data C4. When processing module E reads data B4 from storage module D, data C4 may be stored in storage module D and may be read by processing module E.

[0145] In order to improve the utilization efficiency of the storage resources of the radar device, in some examples, the size of the storage space of the storage module D can be determined according to the amount of sampled data. Exemplarily, the storage space Md of the storage module D can be calculated according to the following formula:

[0146] Md=2×S (4)

[0147] Where S represents the number of sampling points.

[0148] Through the processing of the above-mentioned different links, the speed information, distance information and angle information of the target corresponding to the sampling data A can be output, and the collection of this information can be used as the processing result of the sampling data A, for example, called result data A.

[0149] In the above data processing process, after completing the first processing of sampled data A, processing module A can continue to process sampled data B without waiting for sampled data A to complete the second processing, third processing, fourth processing and fifth processing to generate result data A, and the first processing of processing module A is more efficient. Similarly, after completing the second processing of data A1, processing module B can continue to process data B1 without waiting for data A1 to complete the third processing and fourth processing, and the second processing of processing module B is more efficient. After completing the third processing of data A2, processing module C can continue to process data B2 without waiting for data A2 to complete the fourth processing, and the third processing of processing module C is more efficient. In addition, the fifth processing and the second processing can be performed in parallel. Overall, the above method is more efficient in processing radar signals.

[0150] Based on similar principles, Figure 7 As shown, the embodiment of the present application further provides an agricultural UAV 600 , which may include a power device 610 , a control device 620 , an operating device 630 and a detection device 640 .

[0151] In some examples, the power device 610 can be used to provide power for the flight, operation, etc. of the agricultural drone 600. For example, the power device 610 can include a motor, a propeller, a battery, etc.

[0152] In some examples, the control device 620 can be used to control the flight attitude and navigation of the agricultural drone 600. For example, the control device 620 can include a communication module, a positioning module, an inertial measurement unit, and various sensors such as a barometer and a magnetometer.

[0153] In some examples, the operation device 630 can be used for the operation of the agricultural drone 600. For example, the operation device 630 can be used for spraying pesticides, fertilizers, etc. Exemplarily, the operation device 630 can include a medicine box, a spray head, a flow control valve, a spraying pipeline, and the like.

[0154] In some examples, the detection device 640 can be used for environmental perception and operation control of the agricultural drone 600. For example, the detection device 640 can include the radar device 200 mentioned above. The detection device 640 can also include visual sensors such as cameras, spectral sensors, or humidity sensors.

[0155] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example 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 performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0156] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0157] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0158] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0159] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0160] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0161] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for radar signal processing, characterized in that: Applied to a radar device, the radar device includes a first processing module, a second processing module, a third processing module, a first storage module, a second storage module and a third storage module, and the method includes: The first processing module processes the first data and stores second data in the first storage module, where the second data is a processing result of the first data; The second processing module processes the second data and stores third data in the second storage module, wherein the third data is a first processing result of the second data; The third processing module processes the second data and stores fourth data in the third storage module, where the fourth data is a second processing result of the second data; The first processing module is used to perform range fast Fourier transform processing, the second processing module is used to perform Doppler fast Fourier transform processing, and the third processing module is used to perform direction of arrival estimation processing.

2. The method according to claim 1, characterized in that The size of the first storage module is determined according to the number of sampling points, the number of transmitting antennas, the number of receiving antennas and the number of chirp signals; The size of the second storage module is determined according to the number of sampling points, the number of transmitting antennas, the number of receiving antennas and the number of chirp signals.

3. The method according to claim 1 or 2, characterized in that: The size of the third storage module is determined according to the maximum output target number of the radar signal and the angular accuracy of the radar device.

4. The method according to claim 3, characterized in that: The size of the third storage module is also determined according to the working scenario of the radar device.

5. The method according to claim 4, characterized in that The working scene includes a first target scene and a second target scene. The first target scene satisfies one or more of the following: the terrain is flat, the height difference of the crops is less than or equal to the height threshold, or the planting density of the crops is less than or equal to the density threshold; The second target scene satisfies one or more of the following: the terrain is undulating, the height difference of the crops is greater than the height threshold, or the planting density of the crops is greater than the density threshold; The size of the third storage module corresponding to the first target scene is smaller than the size of the third storage module corresponding to the second target scene.

6. The method according to any one of claims 1 to 5, characterized in that The radar device further includes a fourth processing module, a fifth processing module, a fourth storage module and a fifth storage module, and the method further includes: The fourth processing module processes the third data and stores fifth data in the fourth storage module, wherein the fifth data is a processing result of the third data; The fifth processing module processes the fifth data and stores sixth data in the fifth storage module, wherein the sixth data is a processing result of the fifth data; The fourth processing module is used to perform incoherent combination processing, and the fifth processing module is used to perform constant virtual warning processing.

7. The method according to claim 6, characterized in that The size of the fourth storage module is determined according to the number of sampling points and the number of chirp signals, and the size of the fifth storage module is determined according to the number of sampling points.

8. The method according to any one of claims 1 to 7, characterized in that The first processing module has read permission and write permission for the first storage module, the second processing module has read permission for the first storage module, and the third processing module has read permission for the first storage module.

9. An agricultural drone, characterized in that: It comprises a power device, a radar device and an operating device, wherein the power device is used to provide power for the agricultural UAV, the operating device is used to perform agricultural operations, and the radar device is used to execute the method according to any one of claims 1 to 8.

Images