DBF + LFMCW system zero intermediate frequency radar amplitude-phase high-precision closed-loop near-field calibration system and method

Abstract

The invention relates to a DBF + LFMCW system zero intermediate frequency radar amplitude-phase high-precision closed-loop near-field calibration system and method. The method comprises the following steps: generating a test signal through a target echo simulator; a test signal is connected to a darkroom probe and is aligned with a certain receiving antenna of the radar, the radar equipment assembly receives the signal and mixes the signal with an internal local oscillator signal to obtain a zero intermediate frequency signal received by the channel, and meanwhile, the amplitude and the phase of the zero intermediate frequency signal are periodically collected and output to a terminal interface; a darkroom probe is controlled to be sequentially aligned with 1-N channels of a radar receiving antenna, zero intermediate frequency signals of each channel are collected and stored, recorded zero intermediate frequency data of all the channels are processed through a channel amplitude phase correction algorithm, and accurate correction of each channel is achieved. According to the invention, the baseband I / Q signals are directly collected and processed, so that accurate compensation of I / Q amplitude-phase inherent errors of each channel caused by DC offset, processing technology and the like can be realized.

Description

Technical Field

[0001] The present invention belongs to the field of radio, and in particular relates to a DBF+LFMCW system zero intermediate frequency radar amplitude and phase high-precision closed-loop near-field calibration system and method. Background Art

[0002] In recent years, with the rapid development of drone technology, its application in aerial photography, logistics, agriculture, and other fields has become increasingly widespread. However, the uncontrolled flight of drones also poses serious security risks, such as illegal intrusions into sensitive areas (such as airports, prisons, and military bases), the carrying of dangerous goods to commit crimes, and the disruption of normal aviation operations. According to statistics, the number of security incidents caused by drones is increasing exponentially each year worldwide. In 2024 alone, the scale of my country's anti-drone market reached 2 billion yuan, and is expected to exceed 100 billion yuan by 2035. Therefore, the development of efficient and low-cost drone detection technology has become an urgent need in the security field.

[0003] Traditional drone detection methods (such as optical cameras and radio spectrum monitoring) have significant limitations. Optical cameras are significantly affected by weather and lighting conditions and cannot provide all-weather monitoring. Radio spectrum monitoring is susceptible to interference and has difficulty locating non-cooperative targets. In contrast, radar technology has become the mainstream solution for drone detection due to its environmental freedom, long detection range, and ability to simultaneously obtain target distance and speed information. However, the high cost of traditional phased array radar (a single system can cost over one million yuan) makes it difficult to deploy on a large scale in civilian security scenarios.

[0004] Traditional near-field calibration methods rely on external signal sources and vector network analyzers, which cannot meet these requirements because they cannot provide echo signals synchronized with the radar. Traditional far-field channel amplitude and phase measurement methods, however, have accuracy significantly affected by antenna size and beamwidth. Even with back-end digital amplitude and phase correction, they still cannot meet the requirements for high-precision angle measurement. Furthermore, when the antenna size is too large, it is expensive to establish a far-field test environment. Therefore, addressing the shortcomings of traditional near-field calibration methods is a current issue that needs to be considered. Summary of the Invention

[0005] The purpose of the present invention is to overcome the shortcomings of the prior art and provide a DBF+LFMCW system zero intermediate frequency radar amplitude and phase high-precision closed-loop near-field calibration system to solve the shortcomings of the prior art.

[0006] The object of the present invention is achieved by the following technical solutions: a DBF+LFMCW system zero intermediate frequency radar amplitude and phase high-precision closed-loop near-field calibration system, the system comprising: a radar equipment component, a target echo simulator and a darkroom component; The target echo simulator is used to receive the coherent signal provided by the radar equipment component, generate a test signal after frequency synthesis, and send the test signal to the darkroom component; The chamber assembly is used to amplify the power of the test signal, adjust the position of the chamber probe, and control the probe to sequentially align with receiving channels 1 through N of the radar equipment assembly's receiving antenna. The probe then radiates the amplified test signal to each channel. The radar equipment assembly sequentially stores the baseband data of receiving channels 1 through N and processes this data using a channel amplitude and phase correction algorithm to achieve precise correction of each channel. The radar equipment component is used to send a coherent signal to the target echo simulator, and mix, filter and amplify the received test signal after passing through the darkroom component to generate a zero-intermediate-frequency signal, and then perform analog-to-digital conversion, quantization, encoding and signal processing to complete filtering extraction and FFT operation. After calculating the baseband data of each channel, it is sent to the radar terminal computer through the network switch and the baseband data of the received channel is stored.

[0007] The radar equipment components include a receiving antenna, a receiving front-end device, a mixer, an SFC filter, an amplifier, an A / D converter chip, a signal processing zynq chip and a frequency synthesizer; The frequency synthesizer generates a local oscillator signal, a coherent signal, a sampling clock signal and a coherent reference signal, the coherent signal is sent to the target echo simulator, the local oscillator signal is sent to the mixer, the sampling clock signal is sent to the A / D converter chip, and the coherent reference signal is sent to the signal processing zynq chip; The receiving antenna is connected to the receiving front-end device, the receiving front-end device is connected to the mixer, the mixer, the SFC filter and the amplifier are connected in sequence, and the zero intermediate frequency signal is output to the A / D converter chip. The A / D converter chip performs analog-to-digital conversion, quantization and encoding on the zero intermediate frequency signal and then sends the signal to the signal processing zynq chip. The signal processing zynq chip completes filtering extraction and FFT operation, calculates the baseband data of each channel, and sends the pulse repetition frequency to the frequency synthesizer.

[0008] Before recording the baseband data of each channel, it is necessary to determine whether the amplitude value of the channel is the largest and whether the phase is stable. If the amplitude value is the largest and the phase is stable, the baseband data of the channel is stored in the format of .data file. Finally, the .data files of 1 to N channels are obtained, and the darkroom channel amplitude and phase correction algorithm is called to process the .data files of 1 to N channels.

[0009] The calling of the darkroom channel amplitude and phase correction algorithm to process the .data files of 1 to N channels specifically includes: Select the i-th channel data from channels 1 to N, where i = 1 to N, and construct the raw data vector matrix org.data(M,i) consisting of the IQ values ​​of cycles 1 to M in the i-th channel. If M = 100, the raw data vector matrix of the i-th channel is org.data(100,i); Repeat this loop until all baseband data of all channels are read and all original data vector matrices org.data (M, N) are obtained. Draw the channel amplitude and phase curves. The phase curve uses channel 1 as the reference, and draws the phase differences between the remaining channels and channel 1. The channel amplitude and phase correction algorithm is used to perform amplitude and phase correction on the original data vector matrix org.data (M, N); After completing the channel calibration, simulate and observe the amplitude and phase curves of each channel after calibration; Multiplying the channel correction coefficient by the DBF weight vector to generate a DBF weight containing the channel amplitude and phase correction coefficients, and sending it to the radar equipment component; The radar is powered off and restarted in external trigger mode. The darkroom test system in the darkroom component sends an external trigger pulse to the radar equipment component, controls the darkroom probe to scan the radar receiving array line by line, and tests the near-field radiation pattern of the radar receiving antenna.

[0010] A DBF+LFMCW system zero intermediate frequency radar amplitude and phase high-precision closed-loop near-field calibration method, the method comprising: Step 1: Generate a test signal with the same phase reference as the actual local oscillator signal through the target echo simulator, but with a frequency difference of hundreds of kHz. Step 2: Connect the test signal to the darkroom probe and align it with one of the radar receiving antennas. The radar device receives the signal and mixes it with the internal local oscillator signal to obtain the zero-IF signal received by the channel. At the same time, the amplitude and phase of the zero-IF signal are periodically collected and output to the terminal interface. Step 3: Control the darkroom probe to aim at the 1st to Nth receiving antennas of the radar in turn, collect and store the zero-IF signal of each channel, and process the recorded zero-IF data of all channels through the channel amplitude and phase correction algorithm to achieve accurate correction of each channel.

[0011] The channel amplitude and phase correction algorithm specifically includes: First, obtain the original data vector matrix org.data (M, N); Find the mean value mean(1, N) of each column of the original data vector matrix org.data(M, N), that is, the mean value mean(1, N) of the signal amplitude of each channel 1 to N and M cycles; Select the channel with the largest mean as the benchmark, divide it by org.data (M, N), and use the ratio to generate the channel correction coefficient Junhweight (M, N); Calculate the mean of Junhweight(M,N) over M cycles, use the mean to construct the channel correction matrix, multiply it with org.data(M,N), and perform amplitude and phase correction on each channel; Simulate and observe the effects of channel amplitude and phase correction before and after; The channel correction coefficient is multiplied by the DBF weight vector to generate the DBF weight containing the channel amplitude and phase correction coefficients, and sent to the radar equipment component for subsequent receiving antenna pattern testing.

[0012] The present invention has the following advantages: a high-precision closed-loop near-field amplitude and phase calibration system for a DBF+LFMCW system zero-IF radar, which can accurately compensate for the inherent I / Q amplitude and phase errors of each channel caused by DC offset, processing technology, etc. by directly acquiring and processing baseband I / Q signals; and can also perform receiving antenna pattern testing in a darkroom environment, thereby making up for the reality that the receiving antenna testing methods of the DBF+LFMCW system zero-IF radar are limited. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 This is a block diagram of the channel amplitude and phase correction principle of the present invention; Figure 2 It is a schematic diagram of the zero intermediate frequency data format of 1 to N receiving channels stored in the present invention; Figure 3 This is a screenshot of the channel amplitude and phase displayed on the interface when the darkroom probe stays on a certain channel during the test of the present invention; Figure 4 This is the channel amplitude and phase test and calibration flow chart; Figure 5 It is the amplitude curve of each channel before channel correction; Figure 6 It is the amplitude curve of each channel after channel correction; Figure 7 It is the phase difference curve of each channel before channel correction; Figure 8 It is the phase difference curve of each channel after channel calibration. DETAILED DESCRIPTION

[0014] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the detailed description of the embodiments of the present application provided below in conjunction with the drawings is not intended to limit the scope of protection of the present application for which protection is claimed, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present application. The present invention is further described below in conjunction with the drawings.

[0015] like Figure 1 As shown, one embodiment of the present invention relates to a high-precision closed-loop near-field calibration system for DBF+LFMCW zero-IF radar amplitude and phase based on a fixed target echo simulator. This DBF (digital beamforming) + LFMCW (linear frequency modulated continuous wave) zero-IF radar is an optimal choice for efficient and low-cost drone detection. This radar uses linear frequency modulated continuous wave (LFMCW) signals for transmission, separate transmit and receive antennas, and digital beamforming (DBF) technology for receive elevation. The Zynq signal processing chip processes multi-channel received data to form multiple digital beams. Flexible digital beam pointing is used to achieve coverage of the target airspace.

[0016] The target echo simulator receives the coherent signal provided by the radar's frequency synthesizer. Through frequency synthesis, it generates a test signal several hundred kHz different from the radar's local oscillator signal. This test signal is amplified by an anechoic amplifier before being connected to the anechoic probe. This signal is then aimed at a row of the radar's receiving antennas and mixed with the local oscillator signal provided by the radar's frequency synthesizer by the radar's receiving front end. This signal then passes through the radar's SFC filter and amplifier to generate a zero-IF signal. The radar's A / D converter chip performs analog-to-digital conversion, quantization, and encoding on this zero-IF signal. The signal is then processed by the signal processing chip Zynq, which performs filtering, extraction, and FFT operations to generate baseband data for each channel. This data is then transmitted to the radar terminal computer via a network switch. The operator can save the baseband data for a specific channel by clicking the corresponding button on the radar terminal computer.

[0017] Furthermore, by adjusting the position of the darkroom probe, the darkroom probe is controlled one by one to align with 1 to N receiving channels of the antenna receiving array in sequence, and the baseband information of each channel is stored in sequence.

[0018] See Figure 2~Figure 3 Before recording the baseband data for each channel, observe whether the real-time amplitude and phase values ​​of the channel remain stable, such as Figure 2 As shown, the darkroom probe is now at channel 37, where the amplitude is the largest and the phase is stable. Before recording the baseband data of a channel, it is necessary to ensure that the amplitude of the channel is the largest and the phase is stable. The baseband data format of the stored 1 to N receiving channels is a .data file as shown below. Figure 3 Taking 48 receiving channels as an example, 48 .data files need to be recorded, and the duration of recording each file is about 2s~3s (the specific recording time of each radar device channel data is determined by the PRT duration of the radar device).

[0019] like Figure 4 As shown, the MATLAB darkroom channel amplitude and phase correction algorithm is called to process the .data files of channels 1 to N, specifically including the following: Select the i-th channel data from channels 1 to N, where i = 1 to N, and construct the raw data vector matrix org.data(M,i) consisting of the IQ values ​​of cycles 1 to M in the i-th channel. For example, if M = 100 and N = 48, the raw data vector matrix of the i-th channel is org.data(100,i). Repeat this loop until all baseband data of all channels are read and all original data vector matrices org.data (100, 48) are obtained; Draw the channel amplitude and phase curves. The phase curve uses channel 1 as the reference, and draws the phase differences between the remaining channels and channel 1. The channel amplitude and phase correction algorithm is used to perform amplitude and phase correction on the original data vector matrix org.data (M, N). The channel correction algorithm is specifically described as follows: Find the mean value mean(1, N) of each column of the original data vector matrix org.data(M, N), that is, the mean value mean(1, N) of the signal amplitude of each channel 1 to N and M cycles; Select the channel with the largest mean as the benchmark, divide it by org.data (M, N), and use the ratio to generate the channel correction coefficient Junhweight (M, N); Calculate the mean of Junhweight(M,N) over M cycles, use the mean to construct the channel correction matrix, multiply it with org.data(M,N), and perform amplitude and phase correction on each channel; After completing the channel calibration, simulate and observe the amplitude and phase curves of each channel after calibration; Multiplying the channel correction coefficient by the DBF weight vector to generate a DBF weight containing the channel amplitude and phase correction coefficients, and sending it to the radar equipment component; The radar is powered off and restarted in external trigger mode. The darkroom test system in the darkroom component sends an external trigger pulse to the radar equipment component, controls the darkroom probe to scan the radar receiving array line by line, and tests the near-field radiation pattern of the radar receiving antenna.

[0020] like Figure 5 As shown in the figure, by processing the baseband data of the stored 1~N receiving channels and observing the amplitude curves of each channel before correction, it can be found that before correction, the amplitude of each channel differed by more than 7dB, and the amplitude inconsistency was obvious. Figure 6 As shown in the figure, the amplitude curves of each channel after correction show a maximum difference of 0.1dB, indicating that the amplitude error of the channel has approached 0 after correction.

[0021] like Figure 7 As shown in Figure 2, observing the phase difference curves of each channel before correction, it can be found that before correction, there is a lot of randomness between the phases of each channel, and the inconsistency is obvious. Figure 8 As shown in the figure, observing the phase value curves of each channel after correction, it can be found that after correction, the phase value of each channel is between 28.8° and 29.4°, and the channel phase consistency is high.

[0022] The target echo simulator of the present invention communicates with the radar device through frequency synthesis, and the radar device and the target echo simulator device are disconnected after use. The invention is suitable for the amplitude and phase precision correction and receiving antenna near-field test of mass-produced DBF+LFMCW system zero intermediate frequency radar, thereby reducing the test cost.

[0023] Another embodiment of the present invention relates to a high-precision closed-loop near-field calibration method for the amplitude and phase of a DBF+LFMCW system zero-IF radar based on a fixed target echo simulator. The method can accurately test and calibrate the amplitude and phase of each channel. The method can be widely used in near-field testing of DBF+LFMCW system zero-IF radar receiving antennas to accurately locate faulty channels, calibrate channel amplitude and phase errors, and ensure the full life cycle performance of DBF+LFMCW system zero-IF radar receiving antennas. The method specifically includes the following contents: The first step is to use a target echo simulator to generate a test signal that has the same phase reference as the actual local oscillator signal, but with a frequency difference of hundreds of kHz. In the second step, the test signal is connected to the darkroom probe and aligned with a channel of the radar receiving antenna. The microwave end receives the signal and mixes it with the internal local oscillator signal to obtain the zero intermediate frequency signal received by the channel. The digital end periodically collects the amplitude and phase of the zero intermediate frequency signal and outputs it to the terminal interface. The operator can intuitively see the real-time amplitude and phase values ​​of the channel. Through observation, it was found that as long as the radar is not powered off and restarted, the amplitude and phase of the channel measured when the darkroom probe is moved away and then returned to stay on the array face for multiple times remain basically unchanged, indicating that the amplitude of the test signal generated in the first step is appropriate and the preparation work is complete; The third step is to control the darkroom probe to align with the 1~N channels of the radar receiving antenna in turn. The digital end collects and stores the zero intermediate frequency signal of each channel and calls Figure 4 The channel amplitude and phase correction algorithm process shown processes the zero-IF data of all acquired channels to achieve accurate correction of each channel.

[0024] The fourth step is to observe the channel amplitude and phase simulation results before and after correction to intuitively evaluate the channel amplitude and phase correction effect.

[0025] The foregoing description is merely a preferred embodiment of the present invention. It should be understood that the present invention is not limited to the form disclosed herein and should not be construed as excluding other embodiments. Rather, the present invention is capable of various other combinations, modifications, and improvements, and is capable of modifications within the scope of the concepts described herein, through the above teachings, or through techniques or knowledge in the relevant fields. Modifications and variations made by those skilled in the art that do not depart from the spirit and scope of the present invention are intended to be within the scope of the appended claims.

Claims

1. A high-precision closed-loop near-field calibration system for zero-IF radar amplitude and phase based on a DBF+LFMCW system, characterized by: The system includes: a radar equipment component, a target echo simulator and a darkroom component; The target echo simulator is used to receive the coherent signal provided by the radar equipment component, generate a test signal after frequency synthesis, and send the test signal to the darkroom component; The chamber assembly is used to amplify the power of the test signal, adjust the position of the chamber probe, and control the probe to sequentially align with receiving channels 1 through N of the radar equipment assembly's receiving antenna. The probe then radiates the amplified test signal to each channel. The radar equipment assembly sequentially stores the baseband data of receiving channels 1 through N and processes this data using a channel amplitude and phase correction algorithm to achieve precise correction of each channel. The radar equipment component is used to send a coherent signal to the target echo simulator, and mix, filter and amplify the received test signal after passing through the darkroom component to generate a zero-intermediate-frequency signal, and then perform analog-to-digital conversion, quantization, encoding and signal processing to complete filtering extraction and FFT operation. After calculating the baseband data of each channel, it is sent to the radar terminal computer through the network switch and the baseband data of the received channel is stored.

2. The DBF+LFMCW zero-IF radar amplitude and phase high-precision closed-loop near-field calibration system according to claim 1 is characterized by: The radar equipment components include a receiving antenna, a receiving front-end device, a mixer, an SFC filter, an amplifier, an A / D converter chip, a signal processing zynq chip and a frequency synthesizer; The frequency synthesizer generates a local oscillator signal, a coherent signal, a sampling clock signal and a coherent reference signal, the coherent signal is sent to the target echo simulator, the local oscillator signal is sent to the mixer, the sampling clock signal is sent to the A / D converter chip, and the coherent reference signal is sent to the signal processing zynq chip; The receiving antenna is connected to the receiving front-end device, the receiving front-end device is connected to the mixer, the mixer, the SFC filter and the amplifier are connected in sequence, and the zero intermediate frequency signal is output to the A / D converter chip. The A / D converter chip performs analog-to-digital conversion, quantization and encoding on the zero intermediate frequency signal and then sends the signal to the signal processing zynq chip. The signal processing zynq chip completes filtering extraction and FFT operation, calculates the baseband data of each channel, and sends the pulse repetition frequency to the frequency synthesizer.

3. The DBF+LFMCW zero-IF radar amplitude and phase high-precision closed-loop near-field calibration system according to claim 1 is characterized by: Before recording the baseband data of each channel, it is necessary to determine whether the amplitude value of the channel is the largest and whether the phase is stable. If the amplitude value is the largest and the phase is stable, the baseband data of the channel is stored in the format of .data file. Finally, the .data files of 1 to N channels are obtained, and the darkroom channel amplitude and phase correction algorithm is called to process the .data files of 1 to N channels.

4. The DBF+LFMCW zero-IF radar amplitude and phase high-precision closed-loop near-field calibration system according to claim 3 is characterized by: The calling of the darkroom channel amplitude and phase correction algorithm to process the .data files of 1 to N channels specifically includes: Select the i-th channel data from channels 1 to N, where i = 1 to N, and construct the raw data vector matrix org.data(M,i) consisting of the IQ values ​​of cycles 1 to M in the i-th channel. If M = 100, the raw data vector matrix of the i-th channel is org.data(100,i); Repeat this loop until all baseband data of all channels are read and all original data vector matrices org.data (M, N) are obtained. Draw the channel amplitude and phase curves. The phase curve uses channel 1 as the reference, and draws the phase differences between the remaining channels and channel 1. The channel amplitude and phase correction algorithm is used to perform amplitude and phase correction on the original data vector matrix org.data (M, N); After completing the channel calibration, simulate and observe the amplitude and phase curves of each channel after calibration; Multiplying the channel correction coefficient by the DBF weight vector to generate a DBF weight containing the channel amplitude and phase correction coefficients, and sending it to the radar equipment component; The radar is powered off and restarted in external trigger mode. The darkroom test system in the darkroom component sends an external trigger pulse to the radar equipment component, controls the darkroom probe to scan the radar receiving array line by line, and tests the near-field radiation pattern of the radar receiving antenna.

5. A high-precision closed-loop near-field amplitude and phase calibration method for a DBF+LFMCW zero-IF radar, characterized by: The method comprises: Step 1: Generate a test signal with the same phase reference as the actual local oscillator signal through the target echo simulator, but with a frequency difference of hundreds of kHz. Step 2: Connect the test signal to the darkroom probe and align it with one of the radar receiving antennas. The radar device receives the signal and mixes it with the internal local oscillator signal to obtain the zero-IF signal received by the channel. At the same time, the amplitude and phase of the zero-IF signal are periodically collected and output to the terminal interface. Step 3: Control the darkroom probe to aim at the 1st to Nth receiving antennas of the radar in turn, collect and store the zero-IF signal of each channel, and process the recorded zero-IF data of all channels through the channel amplitude and phase correction algorithm to achieve accurate correction of each channel.

6. The high-precision closed-loop near-field calibration method for DBF+LFMCW zero-IF radar amplitude and phase according to claim 5 is characterized by: The channel amplitude and phase correction algorithm specifically includes: First, obtain the original data vector matrix org.data (M, N); Find the mean value mean(1, N) of each column of the original data vector matrix org.data(M, N), that is, the mean value mean(1, N) of the signal amplitude of each channel 1 to N and M cycles; Select the channel with the largest mean as the benchmark, divide it by org.data (M, N), and use the ratio to generate the channel correction coefficient Junhweight (M, N); Calculate the mean of Junhweight(M,N) over M cycles, use the mean to construct the channel correction matrix, multiply it with org.data(M,N), and perform amplitude and phase correction on each channel; Simulate and observe the effects of channel amplitude and phase correction before and after; The channel correction coefficient is multiplied by the DBF weight vector to generate the DBF weight containing the channel amplitude and phase correction coefficients, and sent to the radar equipment component for subsequent receiving antenna pattern testing.

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