CN112630737A - Preprocessing method for radar intermediate frequency echo signal - Google Patents
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Abstract
The invention provides a preprocessing method of an input intermediate frequency signal. The problem that the output performance of the solid-state transceiving component cannot be tested on the premise that a special testing instrument and radar signal processing software and hardware are not available in the prior art is mainly solved. The scheme is as follows: converting radar real echo signals received by an antenna into multi-channel digital differential signals through analog intermediate-frequency signals subjected to down-conversion by a solid-state transceiving component; leading the differential signal into an MATLAB simulation system, and converting the differential signal into a baseband signal in a down-conversion mode; performing clutter suppression processing according to the echo signal condition of the baseband digital signal, and performing side lobe suppression on the baseband digital signal through time domain pulse pressure processing and windowing; static clutter, sea waves and sleet near zero frequency are suppressed through moving target detection; and selecting different constant false alarm detectors according to the echo edge clutter and noise conditions, then performing clutter suppression, and displaying the result at the terminal. The invention can realize the performance test of the solid-state transceiving component under the condition of no special test instrument and no radar signal processing software and hardware.
Description
Technical Field
The invention belongs to the technical field of signal processing, and particularly relates to a method for processing radar intermediate frequency echo signals, which can be used for detecting the performance of a solid state transceiving component without a radar signal processing software and hardware system.
Background
The pulse compression processing is a mature signal processing technology, and because the wide pulse transmission and the narrow pulse reception are adopted, the contradiction between the action distance and the resolution ratio is better solved. The solid-state transceiver module integrates the functions of an intermediate frequency module, a microwave module and a power amplifier module, and the quality of the performance of the solid-state transceiver module directly influences the pulse compression processing result of subsequent signals and the display effect of terminal radar echoes.
The existing intermediate frequency echo signal processing method of the latent radar comprises the following two steps:
the method is characterized in that for a pulse compression system radar in the latent radar, intermediate frequency echo signals output by the solid state transceiving component through down-conversion are processed through A/D sampling, digital down-conversion, pulse compression processing, MTD processing, constant false alarm and the like.
And secondly, for a frequency modulation continuous wave system radar in the potential radar, the intermediate frequency echo signal output by the solid state transceiving component through down-conversion is processed through A/D sampling, digital down-conversion, FFT processing, MTD processing, constant false alarm and the like.
The two signal processing methods can well complete the real-time processing of the intermediate frequency echo signal, but the performance of the solid-state transceiving component cannot be detected without a radar signal processing software and hardware system and a related testing instrument. Meanwhile, the whole machine joint debugging test is generally carried out after the debugging of each system is finished, and the radar signal processing system is used as the most core part of the radar, so that the design and the debugging are time-consuming in most cases, and therefore, before the design of the radar signal processing system is finished, the performance of the intermediate frequency echo signal output by the solid state transceiving component cannot be preprocessed.
In view of the above problems, in recent years, some methods for detecting solid-state transceiver modules have been proposed in related documents and literature, but most of these methods use a combination of software and hardware of FPGA and DSP or a dedicated test instrument for detection, and little or no preprocessing method application using MATLAB pulse compression simulation is involved. For example, a paper "simulation and application research of pulse compression processing for signal acquisition" in 2013 on modern electronic technology proposes that a standard analog intermediate frequency signal provided by a signal source and an analog intermediate frequency signal output by a standard analog radio frequency signal through down-conversion of a transceiving component are processed by the same digital down-conversion and pulse compression processing methods, so that the performance of the transceiving component is further improved through comparison of processing results, and a new method is provided for performance testing of the transceiving component. However, the method only uses the standard radio frequency signal output by the signal source as the radio frequency echo signal of the radar, and does not describe in detail the preprocessing method of the intermediate frequency echo signal output by the echo signal of the real radar through the down-conversion of the solid state transceiving component. Therefore, the preprocessing of the actually input intermediate frequency echo signal cannot be realized comprehensively and accurately.
Disclosure of Invention
The invention aims to provide a method for preprocessing a radar intermediate frequency echo signal aiming at the defects of the prior art so as to realize the performance detection of the intermediate frequency echo signal output by a solid state transceiving component on the premise of no radar signal processing software and hardware system.
In order to achieve the above purpose, the specific steps of the invention comprise:
(1) setting AD sampling frequency and time sequence, converting real echo signals of the radar into analog intermediate frequency signals through down-conversion of a solid-state transceiving component, and converting the analog intermediate frequency signals into multi-path digital differential signals;
(2) leading the multi-channel digital differential signals into an MATLAB simulation processing system according to a frame synchronization time sequence for down-conversion to obtain baseband digital signals, and judging the condition of received external radio frequency echo signals according to echoes of the baseband digital signals:
if the echo of the baseband digital signal is deteriorated and the interference is increased, inputting the baseband digital signal into a low-pass filter, and optimizing the coefficient and the extraction number of the low-pass filter to complete clutter suppression of the baseband digital signal; otherwise, inputting the baseband digital signal into a low-pass filter, and performing clutter suppression processing on the baseband digital signal according to the coefficient and the extraction number of the fixed low-pass filter;
(3) performing time domain pulse compression processing on the baseband digital signal subjected to clutter suppression processing, and suppressing side lobes of an output signal subjected to time domain pulse compression through windowing processing;
(4) inputting the received baseband digital signals subjected to side lobe suppression into a Moving Target Detection (MTD) processor so as to simultaneously suppress static clutter near zero frequency and low-speed clutter such as sea waves, rain and snow;
(5) receiving the output signal after MTD processing, and selecting subsequent reprocessing according to the output signal condition:
when the output signal after the MTD processing is submerged by the edge clutter and noise, the selection unit selects a large constant false alarm GO-CFAR method on average to carry out clutter suppression on the output signal after the MTD processing;
when the output signal after the MTD processing contains same-frequency asynchronous interference, the selection unit averagely selects a small constant false alarm SO-CFAR method to carry out clutter suppression on the output signal after the MTD processing;
(6) and the receiving unit respectively outputs results after clutter suppression is carried out on the method for averagely selecting the large constant false alarms GO-CFAR by the using unit and the method for averagely selecting the small constant false alarms SO-CFAR by the using unit, and the results are displayed on a terminal display.
Compared with the prior art, the invention has the following advantages:
1. according to the invention, under the condition that no radar signal processing software and hardware system and related test instruments are available, the MATLAB simulation preprocessing method is adopted to acquire real radar intermediate frequency echo signals output by the solid state transceiving component through down-conversion, so that the performance quality detection of the pulse compression system radar solid state transceiving component and the continuous wave system radar solid state transceiving component can be realized.
2. On the premise that the solid-state transceiving component is designed, MATLAB simulation preprocessing is used for flexibly matching the low-pass filter coefficient, the extraction number and the signal processing algorithm, so that the optimal echo performance is realized.
Experiments show that the performance of the pulse compression system and the continuous wave system solid-state transceiving component can be detected through MATLAB simulation pretreatment, and a foundation is laid for further improving the performance of the whole radar.
Drawings
FIG. 1 is a flow chart of an implementation of the present invention;
FIG. 2 is a diagram of a prior MATLAB simulation processing system;
fig. 3 is a diagram showing the results of the echo data and echo pulse compression processing in the present invention.
Detailed Description
The present invention will be described in detail with reference to the following drawings, which are provided for illustration only and not for limiting the present invention.
Referring to fig. 1, the specific implementation steps of the present invention are as follows:
1.1) setting sampling frequency and time sequence parameters of AD sampling equipment, converting real echo signals received by a radar into analog intermediate frequency signals through down-conversion of a solid-state transceiving component, and converting the analog intermediate frequency signals into multi-channel digital differential signals;
1.2) setting a frame synchronization time sequence, and storing the multi-channel digital differential signals strictly according to the frame synchronization time sequence.
And 2, importing the multipath digital differential signals into an MATLAB simulation processing system.
Referring to fig. 2, the MATLAB simulation processing system is composed of an AD sampling storage device, a digital down-conversion DDC processing module, a low-pass filtering processing module, a time domain pulse pressure processing module, a side lobe suppression processing module, a moving target detection MTD processing module, and a constant false alarm CFAR processing module.
And 3, acquiring the baseband digital signal and carrying out clutter suppression according to the echo condition of the baseband digital signal.
Carrying out down-conversion on the multi-channel digital differential signals in an MATLAB simulation processing system to obtain baseband digital signals, and carrying out clutter suppression according to the echo condition of the baseband digital signals:
if the echo of the baseband digital signal is deteriorated and the interference is increased, inputting the baseband digital signal into a low-pass filter, and optimizing the coefficient and the extraction number of the low-pass filter, namely, adopting an equal ripple approximation method, firstly setting an initial frequency point and a passband ripple value, then jointly determining an optimization result according to the signal-to-noise ratio of the baseband signal and the pulse compression effect of the rear end, and finishing clutter suppression of the baseband digital signal;
otherwise, inputting the baseband digital signal into a low-pass filter, and performing clutter suppression processing on the baseband digital signal according to the fixed low-pass filter coefficient and the extraction number.
And 4, compressing and simulating the time domain pulse.
4.1) receiving two paths of input signals X after clutter suppressionIAnd XQ：
XI＝cos(n·f0/fs·2·π).*XT
XQ＝sin(n·f0/fs·2·π).*XT
Wherein n is the number of sampling points, f0Is the center frequency of the signal, fsFor sampling frequency, XTA transposed signal that is X;
4.2) according to two input signals XIAnd XQObtaining a time domain pulse compression input signal x (n):
x(n)＝XI+jXQ
wherein j is a complex number unit;
4,3) inputting the pulse compression input signal x (n) into a matched filter h (n) to obtain a time domain pulse compression output signal y (n):
where x (k) is the sequence signal of the input signal and h (n-k) is the sequence signal of the matched filter.
And 5, performing side lobe suppression simulation processing.
Windowing and suppressing are performed on the sidelobes of the output signal y (n) after the time domain pulse compression processing by using a hamming window function w (f), and a sidelobe suppression processing result is obtained, as shown in fig. 3.
The expression of W (f) is:
where f is the input signal frequency and B is the window function signal spectral width.
Step 6, moving target detection MTD simulation processing
And the moving target detection MTD processing module receives the result of the sidelobe suppression processing, divides the continuous 16-frame echo data into two channels according to the distance units to perform FFT operation in parallel, wherein the first channel processes the first 3000 distance units, the second channel processes the second 3000 distance units, the FFT results of the two channels are subjected to modulus, and the result with the maximum modulus value is used as the output of the distance unit to suppress static clutter, sea waves and rain and snow near the zero frequency to obtain an output signal after MTD processing.
And 7, carrying out CFAR simulation processing on the constant false alarm.
The constant false alarm CFAR simulation processing module receives the output signal after MTD processing, and selects subsequent reprocessing to the output signal according to the output signal condition:
7.1) when the output signal after the MTD processing is submerged by the edge clutter and the noise, the selecting unit selects the large constant false alarm GO-CFAR method on average to carry out clutter suppression on the output signal after the MTD processing, and the implementation is as follows:
7.1.1) sending the input radar data packet into a detector of a unit average selection constant false alarm GO-CFAR in real timeRespectively calculating the real-time mean value Z of the first 6 unit frame signals1And the real-time mean value Z of the last 6 unit frame signals2：
Wherein, | X1iI is the front unit radar data module value, X, of the MTD processed and sent to the unit average selection constant false alarm GO-CFAR detector2iI is a rear unit radar data module value sent into a unit average selection constant false alarm GO-CFAR detector after MTD processing;
7.1.2) calculating the maximum value Z of the detection unit in the GO-CFAR detector in real time according to the calculation result of 7.1.1):
Z＝max(Z1,Z2)；
7.2) when the output signal after MTD processing contains same frequency asynchronous interference, the selecting unit averagely selects a small constant false alarm SO-CFAR method to carry out clutter suppression on the output signal after MTD processing, and the following is realized:
7.2.1) sending the input radar data packet into a detector of a unit average selected constant false alarm SO-CFAR in real time, and respectively obtaining real-time mean values Z 'of the frame signals of the first 6 units'1And real-time mean value Z 'of the last 6 unit frame signals'2：
Wherein, | X'1iL is front unit radar data module value, | X 'in unit average selected constant false alarm SO-CFAR detector after MTD processing'2iI is at MTDThen the data is sent to a unit to averagely select the rear unit radar data modulus value in the constant false alarm SO-CFAR detector;
7.2.2) calculating the minimum value Z' of the detection unit in the SO-CFAR detector in real time according to the calculation result of 7.2.1):
Z′＝min(Z′1,Z′2)。
and 8, outputting results after clutter suppression is respectively carried out on the method for evenly selecting the large constant false alarms GO-CFAR by the using unit and the method for evenly selecting the small constant false alarms SO-CFAR by the using unit, and displaying the results on a terminal display.
The invention provides a new method for the performance test of the solid state transceiving component by acquiring the real radar intermediate frequency echo signal of a certain solid state transceiving component and carrying out MATLAB simulation processing on the data under the condition that a radar signal processing system and a related testing instrument are not provided.
The foregoing description is only an example of the present invention and is not intended to limit the invention, so that it will be apparent to those skilled in the art that various changes and modifications in form and detail may be made therein without departing from the spirit and scope of the invention.
Claims (6)
1.A preprocessing method for radar intermediate frequency echo signals is characterized by comprising the following steps:
(1) setting AD sampling frequency and time sequence, converting real echo signals received by a radar into analog intermediate frequency signals through down-conversion of a solid receiving and transmitting component, and converting the analog intermediate frequency signals into multi-channel digital differential signals;
(2) leading the multi-channel digital differential signals into an MATLAB simulation processing system according to a frame synchronization time sequence for down-conversion to obtain baseband digital signals, and performing clutter suppression processing according to the echo signal condition of the baseband digital signals:
if the echo of the baseband digital signal is deteriorated and the interference is increased, inputting the baseband digital signal into a low-pass filter, and optimizing the coefficient and the extraction number of the low-pass filter to complete clutter suppression of the baseband digital signal;
otherwise, inputting the baseband digital signal into a low-pass filter, and performing clutter suppression processing on the baseband digital signal according to the fixed low-pass filter coefficient and the extraction number;
(3) performing time domain pulse compression processing on the baseband digital signal subjected to clutter suppression processing, and suppressing side lobes of an output signal subjected to time domain pulse compression through windowing processing;
(4) inputting the baseband digital signals subjected to side lobe suppression to a moving target detection MTD processor to simultaneously suppress static clutter near zero frequency and low-speed clutter such as sea waves, rain and snow;
(5) receiving the output signal after MTD processing, and selecting subsequent reprocessing according to the output signal condition:
when the output signal after the MTD processing is submerged by the edge clutter and noise, the selection unit selects a large constant false alarm GO-CFAR method on average to carry out clutter suppression on the output signal after the MTD processing;
when the output signal after the MTD processing contains same-frequency asynchronous interference, the selection unit averagely selects a small constant false alarm SO-CFAR method to carry out clutter suppression on the output signal after the MTD processing;
(6) and the receiving unit respectively outputs results after clutter suppression is carried out on the method for averagely selecting the large constant false alarms GO-CFAR by the using unit and the method for averagely selecting the small constant false alarms SO-CFAR by the using unit, and the results are displayed on a terminal display.
2. The method according to claim 1, wherein the low-pass filter coefficients in (2) are optimized by an equal ripple approximation method, that is, an initial frequency point and a passband ripple value are first set, and then an optimization result is determined according to the signal-to-noise ratio of the baseband signal and the pulse compression effect of the rear end.
3. The method of claim 1, wherein the (3) is implemented as follows:
(3a) receiving the baseband digital signal X after clutter suppression processing in the step (2) to obtain I, Q two paths of demodulated signals XIAnd XQ：
XI＝cos(n·f0/fs·2·π).*XT
XQ＝sin(n·f0/fs·2·π).*XT
In the above formula, n is the number of sampling points, f0Is the center frequency of the signal, fsFor sampling frequency, XTA transposed signal that is X;
(3b) calculating a time domain pulse compression input signal x (n) after the low-pass filtering and decimation processing:
x(n)＝XI+jXQ
wherein j is a complex number unit;
(3c) inputting the pulse compression input signal x (n) into a matched filter h (n) to obtain a time domain pulse compressed output signal y (n):
wherein x (k) is a sequence signal of the input signal, and h (n-k) is a sequence signal of the matched filter;
(3d) windowing and inhibiting the sidelobe of the output signal y (n) after the time domain pulse compression processing by adopting a hamming window function W (f), and obtaining a final pulse compression processing result, wherein the expression of W (f) is as follows:
where f is the input signal frequency and B is the window function signal spectral width.
4. The method according to claim 1, wherein the suppression of stationary clutter near zero frequency and low speed clutter such as sea wave, rain and snow is performed simultaneously in (4), the result of the final pulse compression processing in the receiving (3) is sent to MTD processing, and the continuous 16-frame echo data is divided into two channels according to the distance unit to perform FFT operation in parallel, wherein the first channel processes the first 3000 distance units, the second channel processes the last 3000 distance units, and the FFT results of the two channels are modulo, and the result with the largest modulus value is taken as the output of the distance unit.
5. The method according to claim 1, wherein the selecting unit average selection large constant false alarm GO-CFAR method in (5) performs clutter suppression on the output signal after MTD processing, and is implemented as follows:
5a) the input radar data packet is sent to a detector of a unit average selection constant false alarm GO-CFAR in real time, and the real-time mean value Z of the frame signals of the first 6 units is respectively solved1And the real-time mean value Z of the last 6 unit frame signals2：
Wherein, | X1iI is the front unit radar data module value, X, of the MTD processed and sent to the unit average selection constant false alarm GO-CFAR detector2iI is a rear unit radar data module value sent into a unit average selection constant false alarm GO-CFAR detector after MTD processing;
5b) calculating the maximum value Z of the detection unit in the GO-CFAR detector in real time according to the calculation result of 5 a):
Z＝max(Z1,Z2)。
6. the method according to claim 1, wherein the selecting unit in (5) selects the small constant false alarm SO-CFAR method on average to perform clutter suppression on the output signal after the MTD processing, and is implemented as follows:
5c) the input radar data packet is sent to a detector of unit average selection constant false alarm SO-CFAR in real time, and the real-time mean value Z of the first 6 unit frame signals is respectively calculated1' real-time of the 6 unit frame signalValue Z'2：
Wherein, | X'1iL is front unit radar data module value, | X 'in unit average selected constant false alarm SO-CFAR detector after MTD processing'2iI is a rear unit radar data module value sent into a unit average selection small constant false alarm SO-CFAR detector after MTD processing;
5d) calculating the minimum value Z' of the detection unit in the SO-CFAR detector in real time according to the calculation result of 5 c):
Z'＝min(Z′1,Z′2)。
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