Active phased array radar system for low-altitude unmanned aerial vehicle

Abstract

The invention discloses an active phased array radar system for a low-altitude unmanned aerial vehicle, particularly relates to the field of unmanned aerial vehicles, and comprises a system initialization module, a beam forming calibration module, a received signal noise reduction module, a signal separation and extraction module, a target accurate positioning module, a system parameter optimization module, a data encryption transmission module and a fault monitoring and early warning module. The system initialization module is used for starting an active phased array radar system for initialization, configuring core parameters and establishing a three-dimensional target detection coordinate system; a receiving antenna receives a target reflection signal and amplifies the target reflection signal through a low noise amplifier, an ADC acquisition module executes adaptive noise cancellation and noise reduction processing, and analog-to-digital conversion is carried out on the noise reduction signal to obtain a digital signal sequence; according to the method, the beam pointing precision and gain are remarkably improved, accurate coverage of a low-altitude unmanned aerial vehicle target is ensured, and the azimuth precision of target detection is improved.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) technology, and more specifically, to an active phased array radar system for low-altitude UAVs. Background Technology

[0002] In fields such as low-altitude security, traffic control, and environmental monitoring, active phased array radar has become a core device for low-altitude UAV target detection and monitoring due to its characteristics such as beam agility, multi-target tracking, and high detection accuracy. Existing low-altitude UAV active phased array radar systems typically consist of a radar transmitting module, a receiving module, a data conversion module, a processor module, and an external interface. The transmitting module transmits radar signals, which are reflected by the target and received by the receiving module. Data processing then yields information such as the target's position and velocity, enabling effective detection of low-altitude UAVs.

[0003] Existing active phased array radars have shown certain advantages in low-altitude UAV detection, such as the ability to quickly adjust beam direction to simultaneously track multiple targets, and significantly improved detection efficiency compared to traditional mechanically scanned radars. However, several shortcomings remain in practical applications: First, the transmitting antenna array consists of multiple modules, and the phase and amplitude matching accuracy between and within each module is insufficient, resulting in significant beam pointing deviation and affecting the azimuth accuracy of target detection. Second, the received signal is susceptible to environmental noise and clutter interference; existing noise reduction algorithms are not targeted enough and have limited noise suppression effects, thus reducing the accuracy of target signal extraction. Third, in multi-target detection scenarios, signals from different targets are superimposed, and the lack of efficient signal separation algorithms makes it difficult to accurately obtain the characteristic parameters of individual targets. Fourth, target positioning calculations rely solely on time difference and beam pointing angle, without considering the impact of system hardware errors, and positioning accuracy needs further improvement. Fifth, the operating parameters of each module lack a dynamic optimization mechanism, resulting in a poor balance between power consumption and detection performance. Sixth, the transmitted data is not specifically encrypted, and the transmission parameters are not adjusted according to real-time bandwidth and bit error rate, posing a risk of data leakage and transmission delay. Seventh, there is a lack of real-time fault monitoring and early warning mechanisms for the operating status of each hardware module, resulting in insufficient system stability and reliability.

[0004] To address the shortcomings of existing active phased array radar systems for low-altitude unmanned aerial vehicles (UAVs) in beamforming accuracy, signal processing performance, target positioning accuracy, parameter optimization, data transmission security, and system stability, this invention proposes an active phased array radar system for low-altitude UAVs based on core modules such as a processor module, FPGA data conversion module, radar transmitting module, receiving module, SPI expansion module, and Ethernet / CAN port. This system includes intelligent detection methods for system initialization configuration, transmitting beamforming calibration, receiving signal noise reduction preprocessing, multi-target signal separation, high-precision positioning calculation, dynamic optimization of system parameters, encrypted data transmission, and multi-module fault monitoring. Through the collaborative work of each module and algorithm optimization, the detection performance, stability, and security of the radar system are comprehensively improved. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, the present invention provides an active phased array radar system for low-altitude unmanned aerial vehicles, which solves the problems mentioned in the background art through the following scheme.

[0006] To achieve the above objectives, the present invention provides the following technical solution: an active phased array radar system for low-altitude unmanned aerial vehicles, comprising: System initialization module: Starts the active phased array radar system for initialization, configures core parameters, and establishes a three-dimensional target detection coordinate system; Beamforming calibration module: The processor module controls the radar transmission module through the SPI extension module to construct the beamforming pattern function, and the FPGA data conversion module collects feedback signals to iteratively adjust the phase offset and amplitude attenuation coefficient to complete the calibration. Received signal noise reduction module: The receiving antenna receives the target reflected signal, which is amplified by a low-noise amplifier. The ADC acquisition module performs adaptive noise cancellation and noise reduction processing, and the noise-reduced signal is converted from analog to digital to obtain a digital signal sequence. Signal separation and extraction module: The FPGA data conversion module transmits digital signals to the processor module, and at the same time obtains the signal and noise covariance matrix and performs eigenvalue decomposition to construct a signal separation matrix to separate multiple target signals and extract target feature parameters; Target Precision Positioning Module: The initial straight-line distance of the target is obtained based on the time difference between radar transmission and reception signals. The initial coordinates are obtained by combining the beam pointing angle. A hardware error correction factor is introduced to obtain the corrected distance and derive the precise coordinates of the target. System parameter optimization module: The processor module obtains the working status parameters of each module, constructs the optimization objective function, obtains the optimal parameters by taking the partial derivative, and then performs parameter adjustments through the corresponding module. Data encryption transmission module: The processor module integrates the data to be transmitted, generates an encryption key based on the local oscillator signal frequency and the current timestamp, encrypts the data, transmits it externally through the network port / CAN port, and dynamically adjusts the data block size; Fault monitoring and early warning module: The processor module collects the working status parameters of each hardware module, constructs fault monitoring indicators, obtains the rate of change of the indicators, generates fault early warning signals, and switches to the backup module.

[0007] Preferably, the initialization refers to the post-startup processor module performing initial startup configuration on each hardware module to ensure that each module is in a ready-to-work state; the core parameters include the number of antennas for each radar transmitting module. The total number of sending modules is The number of receiving antennas in the receiving module is Set the local oscillator signal frequency to The radar signal bandwidth is Radar operating wavelength ( (The speed of light in a vacuum), the spacing between the transmitting modules is determined as... The spacing between antenna elements within a single transmitting module is The three-dimensional target detection coordinate system is established with the radar system installation center point as the origin. The preset reference direction for drone flight is set as follows: Axis, perpendicular to The horizontal direction of the axis is The axis, vertically upward is The axis, the real-time coordinates of the target in this coordinate system are represented as: The detection timestamp is recorded as .

[0008] Preferably, the processor module controls the radar transmitting module via the SPI expansion module, specifically including: the processor module outputs a control signal via the SPI expansion module to adjust the operating modes of the four radar transmitting modules and specify the first... The first sending module The phase offset of each antenna is The amplitude attenuation coefficient is The beam pointing angle for target detection is set as the azimuth angle. and pitch angle The beamforming pattern construction function refers to constructing a function characterizing the beam energy distribution. The FPGA data conversion module acquires feedback signals and iteratively adjusts the phase shift and amplitude attenuation coefficients to complete the calibration. Specifically, the FPGA data conversion module acquires the feedback signal after beamforming in real time to obtain the peak beam gain. Compared to sidelobe suppression (The angle corresponding to the sidelobe peak), through repeated adjustments and ,make and Meet the preset performance requirements and complete beamforming calibration.

[0009] Preferably, the receiving antenna receiving the target reflected signal amplified by a low-noise amplifier specifically involves: the eight receiving antennas of the receiving module receiving the radar-transmitted signal reflected by the low-altitude UAV target, and the signal being amplified by a low-noise amplifier; the ADC acquisition module performing adaptive noise cancellation and noise reduction processing specifically involves: determining the first... The original signal received by each receiving antenna is ,in The useful signal reflected by the target. To construct a noise reference signal for the interference signal. Obtain the cross-correlation coefficient between signal and noise: ,in For covariance calculation, for standard deviation To obtain the denoised signal, an adaptive noise cancellation algorithm is used, referencing the standard deviation of the noise signal. The process of performing analog-to-digital conversion on the noise-reduced signal to obtain a digital signal sequence refers to the ADC acquisition module sampling at a frequency... Perform analog-to-digital conversion, with the number of sampling points being... To obtain a digital signal sequence , .

[0010] Preferably, the FPGA data conversion module transmits the digital signal to the processor module specifically by: the FPGA data conversion module transmitting the digital signal acquired by the ADC acquisition module through the MIPI data interface. Transmitted to the processor module; the acquisition of the signal and noise covariance matrix and eigenvalue decomposition refers to assuming that there exists within the detection area. A low-altitude unmanned aerial vehicle target was identified, and the target signal covariance matrix was obtained. Noise covariance matrix For the expected operation, It is a noisy digital signal. (for transpose operation), for Eigenvalues ​​are obtained by performing eigenvalue decomposition. and corresponding feature vectors The specific steps for constructing the signal separation matrix to separate multi-target signals are as follows: selecting the first... The signal subspace is constructed from the eigenvectors corresponding to the largest eigenvalues. Construct the signal separation matrix: ,in To perform the matrix inversion operation, separate the results to obtain the first... Signals for each target: The extraction of target feature parameters refers to the extraction of the first... The magnitude of the characteristic parameters of the target Doppler frequency shift: ,in For frequency variables, For signal duration, Phase calculation operation.

[0011] Preferably, the step of obtaining the initial straight-line distance of the target based on the time difference between radar signal transmission and reception specifically involves defining the radar signal transmission time as... , receive the The time of the target reflected signal is Time difference The initial straight-line distance from the target to the radar: The initial coordinates obtained by combining the beam pointing angle refer to the beam pointing angle. and The initial coordinates of the target are obtained: The specific steps for introducing a hardware error correction factor to obtain the corrected distance are: introducing the phase offset error of the transmitting antenna. and residual noise error of the receiving module Corrected target distance: The specific process for deriving the precise coordinates of the target is as follows: Substituting the initial coordinates into the formula, we obtain the corrected, precise coordinates of the target: .

[0012] Preferably, the processor module obtains the operating status parameters of each module in real time by: the processor module acquiring the first module's operating status parameters in real time through bus data interaction. Power consumption of each transmitting module , No. Signal-to-noise ratio of each receiving module FPGA data processing latency The optimization objective function ,in (Minimum permissible signal-to-noise ratio for the receiving module) (for the maximum allowable processing delay); the optimal parameters obtained by taking partial derivatives refer to... Find them separately $ and Take the partial derivatives and set them equal to 0: The optimal amplitude attenuation coefficient is obtained by solving the problem. and optimal sampling frequency The parameter adjustment, performed by the corresponding module, is executed through the SPI extension module and the ADC acquisition module. and Parameter adjustment.

[0013] Preferably, the processor module integrates the data to be transmitted specifically by: the processor module accurately determining the target coordinates. System operating status parameters are integrated into data to be transmitted. The specific steps of generating an encryption key and encrypting data based on the local oscillator signal frequency and the current timestamp are as follows: based on the local oscillator signal frequency... and current timestamp Generate encryption key The data is encrypted using a symmetric encryption algorithm with a data bit width of [value missing]. The encrypted data: For XOR operation, For modulo operation; the specific steps of transmitting data externally via Ethernet / CAN port and dynamically adjusting the data block size are: transmitting data externally via Ethernet / CAN port. Real-time monitoring of transmission bandwidth and bit error rate Adjust the size of the encrypted data blocks ,make ,in This is a preset minimum transmission rate requirement.

[0014] Preferably, the processor module collects the operating status parameters of each hardware module in real time as follows: the processor module collects the first... Operating temperature of each transmitting module , No. Operating current of each receiving module FPGA logic resource utilization Preset normal working threshold (Normal temperature of the transmitting module) (Normal current of the receiving module) (FPGA normal utilization rate); The construction of fault monitoring indicators refers to the construction of fault monitoring indicators: The obtained rate of change of the indicator refers to the calculation The rate of change of the index is obtained by dividing the change by the change over time. The generation of fault warning signals and switching to the backup module: when When the preset fault change rate threshold is reached, a fault warning signal is generated and sent to the control center via the network port / CAN port, and the backup module is switched to ensure the system continues to work.

[0015] The technical effects and advantages of this invention are as follows: 1. This invention controls the radar transmission module through the SPI extension module and adopts a beamforming calibration method based on the pattern function to adjust the phase and amplitude of each transmission antenna. This solves the problem of beam pointing deviation caused by insufficient phase and amplitude matching accuracy of the transmission antenna array in the prior art, significantly improves beam pointing accuracy and gain, ensures accurate coverage of low-altitude UAV targets, and improves the azimuth accuracy of target detection. 2. The present invention employs an adaptive noise cancellation algorithm in the receiving module, which achieves targeted noise reduction by calculating the cross-correlation coefficient between the signal and noise. At the same time, combined with the high sampling rate conversion of the ADC acquisition module, it solves the problem of low target signal extraction accuracy caused by environmental noise and clutter interference in the prior art, effectively improving the signal-to-noise ratio of the received signal and laying a good foundation for subsequent target signal separation and feature extraction. 3. This invention introduces a multi-target signal separation algorithm based on covariance matrix eigenvalue decomposition into the processor module, constructs a signal separation matrix, and achieves efficient separation of superimposed target signals. It solves the problems of mutual interference between multiple target signals and difficulty in accurately obtaining the feature parameters of a single target in the prior art. It can accurately extract key features such as amplitude and Doppler frequency shift of each target, providing reliable data support for multi-target tracking. 4. In the target positioning calculation, this invention introduces a system hardware error correction factor based on the time difference and beam pointing angle to correct the target distance and coordinates. This solves the problem of insufficient positioning accuracy caused by the failure to consider hardware errors in the prior art, significantly improves the accuracy of target positioning, and meets the high positioning accuracy requirements of low-altitude UAV detection. 5. This invention solves the problems of lack of dynamic optimization of system parameters and poor balance between power consumption and detection performance in the prior art by constructing an objective function that includes power consumption, signal-to-noise ratio and data processing delay, and dynamically optimizing the amplitude of the transmitting antenna and the sampling frequency. Under the premise of ensuring detection performance, it effectively reduces system power consumption and improves the system's endurance and economic efficiency. 6. Before transmitting data externally, this invention generates an encryption key based on the local oscillator signal frequency and the current time, encrypts the data using a symmetric encryption algorithm, and adjusts the data block size according to the real-time transmission bandwidth and bit error rate. This solves the problems of data transmission leakage risk and transmission delay in the prior art, and ensures the security and real-time performance of data transmission. 7. This invention constructs fault monitoring indicators to monitor the operating temperature, current, and logic resource occupancy of each hardware module in real time, and provides fault warnings based on the rate of change of these indicators. This solves the problems of insufficient effective fault monitoring mechanisms and inadequate stability in existing technologies, improves the reliability and continuous working capability of the system, and reduces maintenance costs. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the system structure of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] An active phased array radar system for low-altitude unmanned aerial vehicles (UAVs) includes a processor module, an FPGA data conversion module, an ADC acquisition module, a radar receiving module (including a low-noise amplifier and 8 receiving antennas), four radar transmitting modules (each containing 64 transmitting antennas), an SPI expansion module, a network / CAN port, and a local oscillator signal generation unit. Through multi-module collaborative calibration, signal processing optimization, improved positioning algorithms, and secure transmission design, it addresses the shortcomings of existing technologies. Specifically: Processor Module: The core control and computing unit of the system, responsible for coordinating the collaborative work of various modules and handling complex algorithm calculations. Core functions: Initialize and configure the parameters of each module; receive digital signals transmitted from the FPGA, and perform calculations such as covariance matrix calculation, signal separation, positioning correction, and parameter optimization; generate encryption keys and fault monitoring indicators; output control commands to adjust the working status of each module. Associated Modules: Control the radar transmitting module through the SPI expansion module; receive digital signals transmitted from the FPGA data conversion module; obtain the working status parameters of each module through bus data interaction; output encrypted data and fault warning signals to the network / CAN port.

[0019] FPGA Data Conversion Module: A bridge between data transmission and preprocessing, possessing both high-speed data conversion and interface adaptation capabilities. Core functions: Acquire beamforming feedback signals from the radar transmitter module; receive digital signals from the ADC acquisition module via the MIPI data interface and forward them to the processor module; assist in signal feedback processing during beam calibration. Associated Modules: Receive analog-to-digital conversion signals from the ADC acquisition module; transmit digital signals to the processor module; acquire feedback signals from the radar transmitter module and feed them back to the processor module for calibration.

[0020] ADC Acquisition Module: A key unit for converting analog signals to digital signals, ensuring signal sampling accuracy and rate. Core functions: Performing analog-to-digital conversion on the noise-reduced signal from the receiving module; outputting the digital signal sequence to the FPGA data conversion module; receiving optimal sampling frequency adjustment commands from the processor module. Associated Module: Receives the analog signal from the radar receiving module (after low-noise amplification); outputs the digital signal to the FPGA data conversion module; receives parameter adjustment commands from the processor module.

[0021] Radar receiver module (including low-noise amplifier and 8 receiving antennas): This unit receives and preliminarily processes target reflected signals, including 8 receiving antennas and a low-noise amplifier. Core functions: The 8 receiving antennas capture radar signals reflected from the UAV; the low-noise amplifier amplifies the original signal and suppresses noise interference; the amplified analog signal is transmitted to the ADC acquisition module. - Correlation module: Receives signals transmitted by the radar transmitter module and reflected by the target; outputs amplified analog signals to the ADC acquisition module.

[0022] Radar Transmitting Modules (4 modules, each with 64 transmitting antennas): Directional radar signal transmitting units, totaling 4 modules, each configured with 64 transmitting antennas. Core functions: Generates radar transmission signals based on local oscillator signals; adjusts the phase offset and amplitude attenuation coefficients of each antenna according to processor module instructions to complete beamforming; transmits directional radar signals to the detection area. Associated Modules: Receives local oscillator signals provided by the local oscillator signal generating unit; receives processor control instructions forwarded by the SPI extension module; transmits signals to the detection area; receives target reflection signals, which are then captured by the radar receiving module.

[0023] SPI Expansion Module: A serial communication interface expansion unit that enables command transmission between the processor and the transmitting modules. Core Function: Forwards control commands (phase and amplitude adjustment commands) from the processor module to the four radar transmitting modules; ensures the stability and real-time performance of command transmission. Associated Module: Receives control commands from the processor module; forwards commands to the four radar transmitting modules.

[0024] Network / CAN Port: The system's external data interaction interface, supporting bidirectional data transmission. - Core Functions: Transmits encrypted target data, system operating status parameters, and fault warning signals to an external control center; receives external preset parameters (such as minimum transmission rate). Associated Modules: Receives encrypted data and warning signals output from the processor module; transmits data to an external control center; receives external preset parameters and feeds them back to the processor module.

[0025] Local Oscillator Signal Generation Unit: This unit generates a reference signal, providing a core frequency reference for the transmitting and encryption modules. Its core functions include generating a stable local oscillator signal to provide a signal generation reference to the radar transmitting module and a frequency reference for key generation to the processor module. Associated Module: This module outputs the local oscillator signal to the radar transmitting module and outputs the local oscillator signal frequency parameters to the processor module.

[0026] As attached Figure 1 The active phased array radar system for low-altitude unmanned aerial vehicles shown also includes a system initialization module, a beamforming calibration module, a received signal noise reduction module, a signal separation and extraction module, a target precise positioning module, a system parameter optimization module, a data encryption transmission module, and a fault monitoring and early warning module.

[0027] System initialization module: Starts the active phased array radar system for initialization, configures core parameters, and establishes a three-dimensional target detection coordinate system; In this embodiment, it should be specifically noted that: the initialization refers to the post-startup processor module completing the initial startup configuration of each hardware module to ensure that each module is in a ready-to-work state; the core parameters include the number of antennas in each radar transmitting module. The total number of sending modules is The number of receiving antennas in the receiving module is Set the local oscillator signal frequency to The radar signal bandwidth is Radar operating wavelength ( (The speed of light in a vacuum), the spacing between the transmitting modules is determined as... The spacing between antenna elements within a single transmitting module is The three-dimensional target detection coordinate system is established with the radar system installation center point as the origin. The preset reference direction for drone flight is set as follows: Axis, perpendicular to The horizontal direction of the axis is The axis, vertically upward is The axis, the real-time coordinates of the target in this coordinate system are represented as: The detection timestamp is recorded as Specifically, after system startup and before the official commencement of the low-altitude UAV detection mission, the processor module performs initialization operations within a pre-defined low-altitude detection area. First, the processor module performs initial startup configuration on all hardware modules in the radar system, ensuring each module is ready for operation. Next, it clarifies the core configuration information of each module, including the number of antennas in each radar transmitting module, the total number of transmitting modules, and the number of receiving antennas in the receiving module. It also sets the reference signal frequency, radar signal bandwidth, and radar operating wavelength (calculated based on the speed of light in a vacuum and the reference signal frequency), and determines the spacing between transmitting modules and the spacing between antenna elements within a single transmitting module. Finally, using the radar system's installation center point as the origin, it sets the UAV's flight direction as a pre-defined coordinate axis, the horizontal direction perpendicular to this axis as a second coordinate axis, and the radar's drilling direction as a third coordinate axis, establishing a three-dimensional target detection coordinate system. Simultaneously, it records time stamps during the detection process, providing a basis for subsequent target localization.

[0028] Beamforming calibration module: The processor module controls the radar transmission module through the SPI extension module to construct the beamforming pattern function, and the FPGA data conversion module collects feedback signals to iteratively adjust the phase offset and amplitude attenuation coefficient to complete the calibration. In this embodiment, it should be specifically noted that: the processor module controls the radar transmitting module through the SPI expansion module, specifically including: the processor module outputs control signals through the SPI expansion module to adjust the working modes of the four radar transmitting modules and specify the first... The first sending module The phase offset of each antenna is The amplitude attenuation coefficient is The beam pointing angle for target detection is set as the azimuth angle. and pitch angle The beamforming pattern construction function refers to constructing a function characterizing the beam energy distribution. The FPGA data conversion module acquires feedback signals and iteratively adjusts the phase shift and amplitude attenuation coefficients to complete the calibration. Specifically, the FPGA data conversion module acquires the feedback signal after beamforming in real time to obtain the peak beam gain. Compared to sidelobe suppression (The angle corresponding to the sidelobe peak), through repeated adjustments and ,make and The beamforming calibration is completed to meet preset performance requirements. Specifically, this process is carried out collaboratively by the processor module, SPI extension module, four radar transmission modules (each containing 64 transmitting antennas), and FPGA data conversion module within the low-altitude detection area after system initialization and before the transmission of radar signals to the detection area begins. First, the processor module outputs control signals through the SPI extension module to adjust the operating modes of the four radar transmission modules, defining the phase offset and amplitude attenuation coefficient of each antenna in each transmission module, while simultaneously setting the azimuth and elevation angles for target detection. Next, a radiation pattern function characterizing the beam energy distribution is constructed based on these parameters to guide beamforming. Subsequently, the FPGA data conversion module acquires the feedback signal after beamforming in real time, calculating the peak gain and sidelobe suppression ratio (SPR, the ratio of peak gain to sidelobe peak gain). Finally, the processor module repeatedly adjusts the phase offset and amplitude attenuation coefficient of each antenna based on the calculation results until the peak gain and SPR of the beam meet the preset performance requirements, completing the beamforming calibration and ensuring that the transmitted radar signal accurately covers the detection area.

[0029] Received signal noise reduction module: The receiving antenna receives the target reflected signal, which is amplified by a low-noise amplifier. The ADC acquisition module performs adaptive noise cancellation and noise reduction processing, and the noise-reduced signal is converted from analog to digital to obtain a digital signal sequence. In this embodiment, it should be specifically explained that: the receiving antenna receiving the target reflected signal and amplifying it through a low-noise amplifier specifically means that: the eight receiving antennas of the receiving module receive the radar-transmitted signal reflected by the low-altitude UAV target, and the signal is amplified by a low-noise amplifier; the ADC acquisition module performing adaptive noise cancellation and noise reduction processing specifically means: clarifying the first The original signal received by each receiving antenna is ,in The useful signal reflected by the target. To construct a noise reference signal for the interference signal. Obtain the cross-correlation coefficient between signal and noise: ,in For covariance calculation, for standard deviation To obtain the denoised signal, an adaptive noise cancellation algorithm is used, referencing the standard deviation of the noise signal. The process of performing analog-to-digital conversion on the noise-reduced signal to obtain a digital signal sequence refers to the ADC acquisition module sampling at a frequency... Perform analog-to-digital conversion, with the number of sampling points being... To obtain a digital signal sequence , Specifically, the process involves the radar receiving module (including a low-noise amplifier and eight receiving antennas) and the ADC acquisition module. After the signal transmitted by the radar transmitting module is reflected by the low-altitude UAV target, the signal is processed along the path from the target to the receiving module. First, the eight receiving antennas of the radar receiving module capture the raw radar signal reflected by the UAV target. Next, the raw signal is amplified by the low-noise amplifier within the module, while suppressing some noise interference. Then, the ADC acquisition module determines that the raw signal received by each receiving antenna contains the useful signal reflected by the target and interference signals formed by environmental noise and clutter, constructing a noise reference signal. By calculating the covariance and standard deviation of the useful signal and the noise reference signal, the cross-correlation coefficient between the two is obtained. An adaptive noise cancellation algorithm is then used to subtract the product of the cross-correlation coefficient and the noise reference signal from the raw signal to obtain the denoised signal. Finally, the ADC acquisition module performs analog-to-digital conversion on the denoised signal according to a sampling frequency that meets signal integrity requirements, determines the number of sampling points, and generates a digital signal sequence to prepare for subsequent signal processing.

[0030] Signal separation and extraction module: The FPGA data conversion module transmits digital signals to the processor module, and at the same time obtains the signal and noise covariance matrix and performs eigenvalue decomposition to construct a signal separation matrix to separate multiple target signals and extract target feature parameters; In this embodiment, it should be specifically noted that the FPGA data conversion module transmits the digital signal to the processor module in the following way: the FPGA data conversion module transmits the digital signal acquired by the ADC acquisition module through the MIPI data interface. Transmitted to the processor module; the acquisition of the signal and noise covariance matrix and eigenvalue decomposition refers to assuming that there exists within the detection area. A low-altitude unmanned aerial vehicle target was identified, and the target signal covariance matrix was obtained. Noise covariance matrix For the expected operation, It is a noisy digital signal. (for transpose operation), for Eigenvalues ​​are obtained by performing eigenvalue decomposition. and corresponding feature vectors The specific steps for constructing the signal separation matrix to separate multi-target signals are as follows: selecting the first... The signal subspace is constructed from the eigenvectors corresponding to the largest eigenvalues. Construct the signal separation matrix: ,in To perform the matrix inversion operation, separate the results to obtain the first... Signals for each target: The extraction of target feature parameters refers to the extraction of the first... The magnitude of the characteristic parameters of the target Doppler frequency shift: ,in For frequency variables, For signal duration, Phase calculation is performed. Specifically, after the ADC acquisition module completes the analog-to-digital conversion, the FPGA data conversion module and the processor module execute the calculation within the processor module's processing unit. First, the FPGA data conversion module transmits the digital signal sequence acquired by the ADC to the processor module via the MIPI data interface. Next, assuming the presence of multiple low-altitude UAV targets within the detection area, the processor module calculates the covariance matrix of the target signal and the covariance matrix of the noise digital signal. Eigenvalue decomposition is performed on the sum of the two matrices to obtain a series of eigenvalues ​​and corresponding eigenvectors. Then, the eigenvectors corresponding to the first few largest eigenvalues ​​are selected to construct a signal subspace. Based on this subspace, a signal separation matrix is ​​constructed, and matrix operations are used to separate the superimposed signals of multiple targets into signals of individual targets. Finally, feature parameters are extracted from the signal of each individual target, including the maximum signal amplitude and Doppler frequency shift (obtained by integrating the signal over its duration to solve for the phase, and then combining this with the signal duration), providing data support for target localization.

[0031] Target Precision Positioning Module: The initial straight-line distance of the target is obtained based on the time difference between radar transmission and reception signals. The initial coordinates are obtained by combining the beam pointing angle. A hardware error correction factor is introduced to obtain the corrected distance and derive the precise coordinates of the target. In this embodiment, it should be specifically noted that: the method of obtaining the initial straight-line distance of the target based on the time difference between radar signal transmission and reception specifically means: defining the time of radar signal transmission as... , receive the The time of the target reflected signal is Time difference The initial straight-line distance from the target to the radar: The initial coordinates obtained by combining the beam pointing angle refer to the beam pointing angle. and The initial coordinates of the target are obtained: The specific steps for introducing a hardware error correction factor to obtain the corrected distance are: introducing the phase offset error of the transmitting antenna. and residual noise error of the receiving module Corrected target distance: The specific process for deriving the precise coordinates of the target is as follows: Substituting the initial coordinates into the formula, we obtain the corrected, precise coordinates of the target: Specifically, after extracting the target signal features, the processor module executes the process within the previously established three-dimensional detection coordinate system. First, the processor module records the time the radar transmits the signal and the time it receives the reflected signal from each target, calculates the time difference between the two, and calculates the initial straight-line distance from the target to the radar using the speed of light in a vacuum (the product of the time difference and the speed of light divided by 2). Next, combining the previously set beam pointing angles (azimuth and elevation angles) corresponding to each target, the initial coordinates of the target in the three-dimensional coordinate system are obtained through trigonometric functions. Then, considering potential errors in the hardware operation, the phase offset error of the transmitting antenna and the residual noise error of the receiving module are introduced to correct the initial straight-line distance. During the correction process, the sum of all transmitting antenna phase offset errors is calculated and normalized, and the ratio of the residual noise error to the target signal amplitude is calculated. The corrected target distance is obtained by multiplying the initial distance by the relevant correction coefficient. Finally, the corrected target distance is substituted into the initial coordinate calculation formula to derive the precise coordinates of the target.

[0032] System parameter optimization module: The processor module obtains the working status parameters of each module, constructs the optimization objective function, obtains the optimal parameters by taking the partial derivative, and then performs parameter adjustments through the corresponding module. In this embodiment, it should be specifically noted that: the processor module obtains the working status parameters of each module in real time through bus data interaction. Power consumption of each transmitting module , No. Signal-to-noise ratio of each receiving module FPGA data processing latency The optimization objective function ,in (Minimum permissible signal-to-noise ratio for the receiving module) (for the maximum allowable processing delay); the optimal parameters obtained by taking partial derivatives refer to... Find them separately $ and Take the partial derivatives and set them equal to 0: The optimal amplitude attenuation coefficient is obtained by solving the problem. and optimal sampling frequency The parameter adjustment, performed by the corresponding module, is executed through the SPI extension module and the ADC acquisition module. and The parameter adjustment is specifically performed by the processor module, SPI expansion module, and ADC acquisition module in a coordinated manner during the continuous detection task after the target is accurately located. First, the processor module acquires real-time operating status parameters such as power consumption of each transmitting module, signal-to-noise ratio of each receiving module, and FPGA data processing delay through bus data interaction. Next, it constructs an optimization objective function including power consumption, signal-to-noise ratio, and processing delay, introducing coefficients related to the maximum or minimum allowable values ​​of each parameter to ensure that all terms of the function are dimensionless, guaranteeing the rationality of the optimization logic. Then, it calculates the partial derivatives of the optimization objective function with respect to the amplitude attenuation coefficient of the transmitting antenna and the sampling frequency of the ADC, setting the partial derivatives to zero, and solves the equations to obtain the optimal amplitude attenuation coefficient and sampling frequency for the objective function. Finally, the processor module sends the optimal amplitude attenuation coefficient command to each transmitting module via the SPI expansion module, and the ADC acquisition module adjusts the sampling frequency to achieve the optimal balance between system power consumption and detection performance.

[0033] Data encryption transmission module: The processor module integrates the data to be transmitted, generates an encryption key based on the local oscillator signal frequency and the current timestamp, encrypts the data, transmits it externally through the network port / CAN port, and dynamically adjusts the data block size; In this embodiment, it should be specifically noted that the processor module integrates the data to be transmitted in the following way: the processor module accurately calculates the target coordinates. System operating status parameters are integrated into data to be transmitted. The specific steps of generating an encryption key and encrypting data based on the local oscillator signal frequency and the current timestamp are as follows: based on the local oscillator signal frequency... and current timestamp Generate encryption key The data is encrypted using a symmetric encryption algorithm with a data bit width of [value missing]. The encrypted data: For XOR operation, For modulo operation; the specific steps of transmitting data externally via Ethernet / CAN port and dynamically adjusting the data block size are: transmitting data externally via Ethernet / CAN port. Real-time monitoring of transmission bandwidth and bit error rate Adjust the size of the encrypted data blocks ,make ,in To preset a minimum transmission rate requirement, specifically, after system parameter optimization and when feedback of detection results is needed, the processor module and the Ethernet / CAN port execute the following steps in the data interaction channel between the system and the external control center: First, the processor module integrates the precise coordinates of each target and the operating status parameters of each system module into data to be transmitted. Next, based on the reference signal frequency provided by the local oscillator signal generator and the current detection timestamp, an encryption key is generated using the SHA-256 hash function. A symmetric encryption algorithm is then used to encrypt the integrated data to be transmitted. During encryption, it is necessary to ensure that the key and data bit width are consistent. The key format is adjusted through modulo operations, and then the encrypted data is obtained through XOR operations. Then, the encrypted data is transmitted to the external control center via the Ethernet / CAN port. Finally, during transmission, the transmission bandwidth and bit error rate are monitored in real time. Based on the monitoring results, the block size of the encrypted data is adjusted to ensure that the product of the transmission bandwidth and the data block size divided by the bit error rate meets the preset minimum transmission rate requirement, thus guaranteeing the real-time performance and security of data transmission.

[0034] Fault monitoring and early warning module: The processor module collects the working status parameters of each hardware module, constructs fault monitoring indicators, obtains the rate of change of the indicators, generates fault early warning signals, and switches to the backup module.

[0035] In this embodiment, it should be specifically noted that: the processor module collects the working status parameters of each hardware module in real time as follows: the processor module collects the first... Operating temperature of each transmitting module , No. Operating current of each receiving module FPGA logic resource utilization Preset normal working threshold (Normal temperature of the transmitting module) (Normal current of the receiving module) (FPGA normal utilization rate); The construction of fault monitoring indicators refers to the construction of fault monitoring indicators: The obtained rate of change of the indicator refers to the calculation The rate of change of the index is obtained by dividing the change by the change over time. The generation of fault warning signals and switching to the backup module: when When a preset fault change rate threshold is reached, a fault warning signal is generated and sent to the control center via the Ethernet / CAN port, and a backup module switchover is initiated to ensure continuous system operation. Specifically, the processor module and the Ethernet / CAN port continuously execute the system's detection process under the operating conditions of each hardware module. First, the processor module collects the operating temperature of each transmitting module, the operating current of each receiving module, and the logic resource utilization rate of the FPGA in real time, while presetting normal operating thresholds for each parameter, including the normal operating temperature of the transmitting module, the normal operating current of the receiving module, and the normal logic resource utilization rate of the FPGA. Next, a fault monitoring index is constructed, which is the sum of the squares of the differences between the operating temperature and normal temperature of each transmitting module, the sum of the squares of the differences between the operating current and normal current of each receiving module, and the sum of the squares of the differences between the FPGA logic resource utilization rate and normal utilization rate. Then, the rate of change of this fault monitoring index over time is calculated. Finally, when the rate of change of the index exceeds the preset fault change rate threshold, the processor module generates a fault warning signal, sends it to the external control center via the Ethernet / CAN port, and simultaneously initiates the backup module switchover process to ensure that the system can continuously and stably execute the detection task.

[0036] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An active phased array radar system for low-altitude unmanned aerial vehicles, characterized in that, include: System initialization module: Starts the active phased array radar system for initialization, configures core parameters, and establishes a three-dimensional target detection coordinate system; Beamforming calibration module: The processor module controls the radar transmission module through the SPI extension module to construct the beamforming pattern function, and the FPGA data conversion module collects feedback signals to iteratively adjust the phase offset and amplitude attenuation coefficient to complete the calibration. Received signal noise reduction module: The receiving antenna receives the target reflected signal, which is amplified by a low-noise amplifier. The ADC acquisition module performs adaptive noise cancellation and noise reduction processing, and the noise-reduced signal is converted from analog to digital to obtain a digital signal sequence. Signal separation and extraction module: The FPGA data conversion module transmits digital signals to the processor module, and at the same time obtains the signal and noise covariance matrix and performs eigenvalue decomposition to construct a signal separation matrix to separate multiple target signals and extract target feature parameters; Target Precision Positioning Module: The initial straight-line distance to the target is obtained based on the time difference between radar transmission and reception signals. The initial coordinates are obtained by combining the beam pointing angle. A hardware error correction factor is introduced to obtain the corrected distance and derive the precise coordinates of the target. System parameter optimization module: The processor module obtains the working status parameters of each module, constructs the optimization objective function, obtains the optimal parameters by taking the partial derivative, and then performs parameter adjustments through the corresponding module. Data encryption transmission module: The processor module integrates the data to be transmitted, generates an encryption key based on the local oscillator signal frequency and the current timestamp, encrypts the data, transmits it externally through the network port / CAN port, and dynamically adjusts the data block size; Fault monitoring and early warning module: The processor module collects the working status parameters of each hardware module, constructs fault monitoring indicators, obtains the rate of change of the indicators, generates fault early warning signals, and switches to the backup module.

2. The active phased array radar system for low-altitude unmanned aerial vehicles according to claim 1, characterized in that: The initialization refers to the post-startup processor module performing initial startup configuration on each hardware module to ensure that each module is in a ready-to-work state; the core parameters include the number of antennas for each radar transmitting module. The total number of sending modules is The number of receiving antennas in the receiving module is Set the local oscillator signal frequency to The radar signal bandwidth is Radar operating wavelength The spacing between the sending modules is determined to be... The spacing between antenna elements within a single transmitting module is ; The three-dimensional target detection coordinate system is established with the radar system installation center point as the origin. The preset reference direction for drone flight is set as follows: Axis, perpendicular to The horizontal direction of the axis is The axis, vertically upward is The axis, the real-time coordinates of the target in this coordinate system are represented as: , For detecting timestamps.

3. The active phased array radar system for low-altitude unmanned aerial vehicles according to claim 2, characterized in that: The processor module controls the radar transmitting modules via the SPI expansion module, specifically by: the processor module outputting control signals through the SPI expansion module to adjust the operating modes of the four radar transmitting modules and specifying the first... The first sending module The phase offset of each antenna is The amplitude attenuation coefficient is The beam pointing angle for target detection is set as the azimuth angle. and pitch angle The beamforming pattern construction function refers to constructing a function characterizing the beam energy distribution. The FPGA data conversion module acquires feedback signals and iteratively adjusts the phase shift and amplitude attenuation coefficients to complete the calibration. Specifically, the FPGA data conversion module acquires the feedback signal after beamforming in real time to obtain the peak beam gain. Compared to sidelobe suppression Through repeated adjustments and ,make and Meet the preset performance requirements and complete beamforming calibration.

4. The active phased array radar system for low-altitude unmanned aerial vehicles according to claim 1, characterized in that: The receiving antennas receive the target reflected signal and amplify it using a low-noise amplifier. Specifically, the eight receiving antennas of the receiving module receive the radar-transmitted signal reflected by the low-altitude UAV target, and the signal is amplified by a low-noise amplifier. The ADC acquisition module performs adaptive noise cancellation and noise reduction processing. Specifically, it determines the first... The original signal received by each receiving antenna is ,in The useful signal reflected by the target. To construct a noise reference signal for the interference signal. Obtain the cross-correlation coefficient between signal and noise: The noise-reduced signal is obtained using an adaptive noise cancellation algorithm: The process of converting the denoised signal to a digital signal sequence via analog-to-digital conversion refers to the ADC acquisition module sampling at a frequency... Perform analog-to-digital conversion, with the number of sampling points being... To obtain a digital signal sequence , .

5. The active phased array radar system for low-altitude unmanned aerial vehicles according to claim 1, characterized in that: The FPGA data conversion module transmits digital signals to the processor module specifically by: the FPGA data conversion module transmitting the digital signals acquired by the ADC acquisition module through the MIPI data interface. Transmitted to the processor module; the acquisition of the signal and noise covariance matrix and eigenvalue decomposition refers to assuming that there exists within the detection area. A low-altitude unmanned aerial vehicle target was identified, and the target signal covariance matrix was obtained. Noise covariance matrix ,right Eigenvalues ​​are obtained by performing eigenvalue decomposition. and corresponding feature vectors The specific steps for constructing the signal separation matrix to separate multi-target signals are as follows: selecting the first... The signal subspace is constructed from the eigenvectors corresponding to the largest eigenvalues. Construct a signal separation matrix Separation yields the first Signal of the target The extraction of target feature parameters refers to the extraction of the first... The magnitude of the characteristic parameters of the target Doppler frequency shift .

6. The active phased array radar system for low-altitude unmanned aerial vehicles according to claim 1, characterized in that: The method of obtaining the initial straight-line distance of the target based on the time difference between radar transmitted and received signals specifically involves defining the radar signal transmission time as follows: , receive the The time of the target reflected signal is Time difference The initial straight-line distance from the target to the radar: The initial coordinates obtained by combining the beam pointing angle refer to the beam pointing angle. and The initial coordinates of the target are obtained: The specific steps for introducing a hardware error correction factor to obtain the corrected distance are: introducing the phase offset error of the transmitting antenna. and residual noise error of the receiving module Corrected target distance: The specific process for deriving the precise coordinates of the target is as follows: Substituting the initial coordinates into the formula, we obtain the corrected, precise coordinates of the target: .

7. The active phased array radar system for low-altitude unmanned aerial vehicles according to claim 1, characterized in that: The processor module acquires the operating status parameters of each module in real time by: the processor module acquiring the parameters through bus data interaction. Power consumption of each transmitting module , No. Signal-to-noise ratio of each receiving module FPGA data processing latency The optimization objective function The method of obtaining the optimal parameters by taking partial derivatives refers to... Find them separately $ and Take the partial derivatives and set them equal to 0: The optimal amplitude attenuation coefficient is obtained by solving the problem. and optimal sampling frequency The parameter adjustment is performed by the corresponding module through the SPI extension module and the ADC acquisition module. and Parameter adjustment.

8. The active phased array radar system for low-altitude unmanned aerial vehicles according to claim 1, characterized in that: The processor module integrates the data to be transmitted specifically by: the processor module accurately determining the target coordinates. System operating status parameters are integrated into data to be transmitted. The specific steps of generating an encryption key and encrypting data based on the local oscillator signal frequency and the current timestamp are as follows: based on the local oscillator signal frequency... and current timestamp Generate encryption key The data is encrypted using a symmetric encryption algorithm with a data bit width of [missing information]. encrypted data The specific steps of transmitting data externally via Ethernet / CAN port and dynamically adjusting the data block size are: transmitting data externally via Ethernet / CAN port. Real-time monitoring of transmission bandwidth and bit error rate Adjust the size of encrypted data blocks ,make ,in This is a preset minimum transmission rate requirement.

9. The active phased array radar system for low-altitude unmanned aerial vehicles according to claim 1, characterized in that: The processor module collects the operating status parameters of each hardware module in real time, specifically as follows: the processor module collects the first... Operating temperature of each transmitting module , No. Operating current of each receiving module FPGA logic resource utilization Preset normal temperature of the transmitting module Normal current of the receiving module FPGA normal utilization rate The construction of fault monitoring indicators refers to the construction of fault monitoring indicators: The obtained rate of change of the indicator refers to the calculation The rate of change of the index is obtained by dividing the change by the change over time. The generation of fault warning signals and switching to the backup module: when hour, To preset the fault change rate threshold, a fault warning signal is generated and sent to the control center via the network port / CAN port, and a backup module is activated to ensure continuous system operation.

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