CN111796288B - Clutter frequency spectrum compensation technology-based three-coordinate radar moving target processing method - Google Patents
Clutter frequency spectrum compensation technology-based three-coordinate radar moving target processing method Download PDFInfo
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- CN111796288B CN111796288B CN202010536220.1A CN202010536220A CN111796288B CN 111796288 B CN111796288 B CN 111796288B CN 202010536220 A CN202010536220 A CN 202010536220A CN 111796288 B CN111796288 B CN 111796288B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/95—Radar or analogous systems specially adapted for specific applications for meteorological use
- G01S13/958—Theoretical aspects
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/66—Radar-tracking systems; Analogous systems
- G01S13/68—Radar-tracking systems; Analogous systems for angle tracking only
- G01S13/685—Radar-tracking systems; Analogous systems for angle tracking only using simultaneous lobing techniques
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
- G01S7/414—Discriminating targets with respect to background clutter
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Abstract
The invention belongs to the field of radar signal processing, and relates to a three-coordinate radar moving target processing method based on a clutter frequency spectrum compensation technology, which is used for improving the elevation angle measurement precision in a strong ground clutter environment. Windowing DFT (discrete Fourier transform) is carried out on each distance bin pulse group data of each elevation layer to calculate an initial frequency spectrum; acquiring the maximum spectral line amplitude and speed information of the initial spectrum, reconstructing a virtual clutter spectrum according to the information, and subtracting the virtual clutter spectrum from the initial spectrum to obtain a compensated spectrum, namely a new spectrum; iteratively calculating the maximum spectral line amplitude and speed of the new spectrum, reconstructing a virtual clutter spectrum according to the information, subtracting the virtual clutter spectrum from the new spectrum until the maximum spectral line amplitude of the new spectrum is less than K times of the noise level, and recording the iterative estimation result of each time; and (4) performing constant false alarm processing on each channel of the DFT, and selecting final output according to the constant false alarm detection result and a preset speed threshold. The invention recovers the relative relation of target energy on different elevation layers by compensating clutter energy for multiple times, and improves the elevation angle measurement precision.
Description
Technical Field
The invention relates to the technical field of radar signal processing.
Background
The radar is often used with a weapon system as a detection instrument, and compared with the traditional two-coordinate radar, the three-coordinate radar provides height information of a target and can provide three-dimensional eye finger information for the weapon system. The elevation measurement accuracy index is therefore an important parameter for radar. Modern three-coordinate radars are often implemented by using a phase-scanning system, and elevation measurement is based on relative amplitude information between sum and difference beams or DBF multi-beams. However, the environment of the radar is complex, and the echo often has strong clutter energy (such as ground clutter and weather clutter). Due to the fact that clutter energy is distributed inconsistently on different elevation angle layers, relative amplitude information among wave beams is changed, and elevation angle accuracy of a radar detection target is affected. In order to suppress clutter energy, a modern radar usually adopts a coherent system and a Doppler moving target algorithm is used for suppressing a clutter frequency spectrum. Due to the existence of the transition band of the filter, no matter the traditional single notch filter algorithm, or the self-adaptive MTI and MTD algorithm using the multi-notch filter or the clutter map technology, when the target amplitude is lower than the clutter amplitude and the target and the clutter are very close to each other in the frequency domain, the target energy cannot be effectively extracted.
In order to solve the problem that ground clutter submerges zero-speed meteorological echoes in the existing meteorological radar, the influence of the ground clutter and the recovery meteorological echoes is realized by adopting a GMAP (pulse-amplitude-pulse-width modulation) algorithm or an SSEF (steady state pulse-width modulation) filter algorithm, the two algorithms can recover meteorological information through iteration, but the two algorithms utilize the characteristic that the spectral width of the meteorological clutter is wide, and the zero-speed meteorological echoes are recovered through Gaussian fitting by utilizing meteorological residual spectral energy. However, the target does not have such a spectral width characteristic, and the target spectral energy submerged by the clutter spectrum cannot be recovered by using the residual spectral energy of the target. Thus, using the prior art, clutter energy can overwhelm target energy and cause inaccurate elevation measurements. This phenomenon occurs very frequently in the detection of low altitude weak targets.
Disclosure of Invention
The invention aims to design a three-coordinate radar moving target processing method based on a clutter frequency spectrum compensation technology, and optimizes the problem of poor elevation angle measurement precision caused by target elevation angle measurement jumping due to inconsistent distribution of clutter energy in different elevation angle layers in a strong clutter environment.
The technical solution for realizing the purpose of the invention is as follows:
1) let x be ═ x1 x2 ... xn]Windowing X for related pulse time sequence vectors of the same distance unit of a certain elevation angle layer of the radar, and performing N-point DFT on windowed data to obtain an N-point DFT result X' (K), wherein K belongs to [ 12.. N ]](ii) a Taking an absolute value of X' (K) to obtain X (K); finding the maximum X (l) of X (K) and the spectral width σ around X (l)wEnergy lines in the range, denoted as [ X (l- σ) ]w/2)...X(l)...X(l+σw/2)]，σwThe clutter division type setting can be adopted;
2) for [ X (l-sigma) ]w/2)...X(l)...X(l+σw/2)]Calculating the maximum value X (l) for the frequency value Fk by means of a weighting algorithm0According to Fk0And X (l), calculating an Fk under ideal conditions0DFT spectrum of N after windowing of complex signal with frequency and intensity of X (l)
Mixing X (K) with
Subtracting to obtain Doppler spectrum compensated spectrum Xc(K)
3) Mixing Xc(K) Dividing the Doppler signals into high, medium and low 5 areas according to the Doppler velocity and different Doppler directions, calculating the average value of spectral lines of the 5 areas, and taking the minimum average value as a noise level;
4) let the frequency spectrum of the mth iteration be denoted as Xcm(K) The maximum in the spectrum is denoted Xcm(l'), if Xcm(l') greater than 2 times the noise level, and calculating the maximum value X by a maximum-near spectral line weighting algorithmcm(l') for frequency value Fk1(m) according to Fk1(m) and Xcm(l') calculating an Fk under ideal conditions1(m) frequency, intensity Xcm(l') DFT spectrum of N after complex signal windowing
Mixing Xcm(K) And
subtracting to obtain Doppler spectrum compensated spectrum Xcm+1(K) (ii) a Repeating the step 4 until Xcm(l') less than 2 times the noise level;
5) processing the X (K) in distance by using unit average constant false alarm rate if the current distance is the Fk calculated in the step 2)0The corresponding Doppler channel is over-constant false alarm threshold, and Fk is used0Larger than the preset speed threshold, selecting Fk in the step 2)0And X (l) as output; otherwise, if step 4) Fk1(m) the corresponding Doppler channel crosses the constant false alarm threshold, and Fk1(m) is greater thanPreset speed threshold output Xcm(l'), otherwise, outputting the noise level calculated in the step 3); and finally, calculating elevation values of the same distance unit data of different elevation layers according to a conventional method.
The method can restore the relative relation of target energy on different elevation layers in a mode of compensating clutter energy for many times when the target time domain is submerged by the clutter and the frequency domain is very close to the clutter, thereby improving the elevation angle measurement precision of the three-coordinate radar.
Drawings
Fig. 1 is a flow chart of the calculation.
Fig. 2 is a schematic diagram of spectral compensation.
FIG. 3 is a diagram of simulation effect of weak targets passing through clutter of ground objects.
FIG. 4 is a diagram of the simulation effect of elevation measurement of clutter of weak targets passing through the ground.
Detailed Description
The invention is further explained below with reference to the figures and examples.
The implementation process of the embodiment of the invention is as follows:
1) as shown in fig. 1, let x ═ x1 x2 ... xn]Windowing X for a time sequence vector of related pulses of the same distance unit of a certain elevation angle layer of the radar, and performing N-point DFT on windowed data to obtain an N-point DFT result X' (K), wherein K belongs to [ 12.. n.. N ]](ii) a Taking an absolute value of X' (K) to obtain X (K); finding the maximum X (l) of X (K) and the spectral width σ around X (l)wEnergy lines in the range, denoted as [ X (l- σ) ]w/2)...X(l)...X(l+σw/2)]，σwThe clutter division type setting can be adopted;
dividing three-coordinate radar data into data of different elevation layers after orthogonal down-conversion and digital beam forming, storing IQ data of each layer into a matrix according to distance and pulse forms after pulse compression, wherein x is [ x ═ x [ ]1 x2 ... xn]The related pulses of the same range bin at a certain elevation layer. And windowing the X, performing N-point DFT on the windowed data to obtain an N-point DFT result X '(K), and taking an absolute value of the X' (K) to obtain X (K). Wherein the windowing function may be selected according to actual requirements,this embodiment uses a hanning window. Where X' (K) can be computed using FFT when N is a power of 2. In this example, N is 16. Then find the maximum value X (l) of X (K) and record its index l. When l is near zero frequency, it represents X (l) as ground clutter spectrum, when σwA preset ground clutter spectrum width value can be adopted, and the ground clutter spectrum width value is set to be 2 in the embodiment; when l is not near zero frequency, it represents that X (l) may be meteorological clutter frequency spectrum, and then sigmawA preset meteorological clutter frequency spectrum can be adopted, and the value of the meteorological clutter frequency spectrum is set to be 4 in the embodiment;
2) as shown in FIG. 2, for [ X (l- σ)w/2)...X(l)...X(l+σw/2)]Calculating the maximum value X (l) for the frequency value Fk by using a weighting algorithm or a multiline interpolation algorithm0According to Fk0And X (l), calculating an Fk under ideal conditions0DFT spectrum of N after windowing of complex signal with frequency and intensity of X (l)
Mixing X (K) with
Subtracting to obtain Doppler spectrum compensated spectrum Xc(K)；
The implementation adopts a frequency domain weighting algorithm to calculate Fk0I.e. by
Calculating an Fk under ideal conditions0Complex signal with frequency and intensity of X (l)
Windowed N DFT spectrum
Wherein
w (n) is a window function. Mixing X (K) with
Subtracting to obtain Doppler spectrum compensated spectrum Xc(K)；
3) Mixing Xc(K) Dividing the Doppler signals into high, medium and low 5 areas according to the Doppler velocity and different Doppler directions, calculating the average value of spectral lines of the 5 areas, and taking the minimum average value as a noise level;
when N is 16, the DFT output channel is selected [ 1314150123 ]]For the low speed region, DFT output channel [ 345 ]]Forward direction medium speed region, DFT output channel [ 567 ]]A positive direction high speed area; DFT output channel [ 111213]Negative direction medium speed region, DFT output channel [ 8910 ]]Is a negative direction high speed region. The average value of 5 areas in high, middle and low is obtained, and the minimum value is taken as the noise level Anoise。
4) Let the frequency spectrum of the mth iteration be denoted as Xcm(K) The maximum in the spectrum is denoted Xcm(l'), if Xcm(l') greater than 2 times noise level, and calculating maximum value X by maximum value near spectral line weighting algorithmcm(l') for frequency value Fk1(m) according to Fk1(m) and Xcm(l') calculating an Fk under ideal conditions1(m) frequency, intensity Xcm(l') DFT spectrum of N after complex signal windowing
Mixing Xcm(K) And
subtracting to obtain Doppler spectrum compensated spectrum Xcm+1(K) (ii) a Repeating the step 4 until Xcm(l') less than 2 times the noise level. Wherein Fk1(m) maximum-vicinity spectral width σ 'may be employed'wThe spectral line weighting algorithm of (1) obtains the spectral width sigma 'of the new spectrum'wThe calculation method is that the left side is taken k by taking l' as the center1Number of, satisfy simultaneously, Xcm(l'-k+1)＜Xcm(l'-k)，Xcm(l`-k)＞2Anoise，k∈[1k1](ii) a Get k to the right2Number of, satisfy simultaneously, Xcm(l`+k)＞Xcm(l`+k+1)，Xcm(l`+k)＞2Anoise，k∈[1k2]. The data set satisfying the condition is recorded as [ X ]cm(l`-k1)...Xcm(l`)...Xcm(l`+k2)]Using a weighted algorithm
5) Adopting constant false alarm processing on the distance of X (K), if the current distance unit has Fk calculated in step 2)0The corresponding Doppler channel is over-constant false alarm threshold, and Fk is used0Larger than the preset speed threshold, selecting Fk in the step 2)0And X (l) as output; otherwise, if step 4) Fk1(m) the corresponding Doppler channel crosses the constant false alarm threshold, and Fk1(m) greater than a predetermined speed threshold output Xcm(l'), otherwise, outputting the noise level calculated in the step 3); in this example, the speed threshold is set to 2 m/s; and finally, calculating elevation values of the same distance unit data of different elevation layers according to a conventional method. For a DBF three-coordinate radar, weighted calculation is adopted for elevation angle calculation.
Where i is the channel number for elevation, θ, of the maximum data for different elevation layersnFor spatial directional values of the respective elevation angles, AnAmplitude values at different elevations. Theta is a measure of the target elevation angle. As shown in FIG. 3, due to the existence of strong ground objects, the distribution of the ground object energy in different elevation layers is inconsistent, the distribution relation of the target energy in the space is destroyed, and the height measurement value is inaccurate by adopting the traditional condensation method. By adopting the traditional moving target algorithm, ground clutter cannot be eliminated under the condition of not influencing the target intensity; by adopting the method and the device, the influence of the ground object energy on different elevation layers is eliminated through ground object clutter frequency spectrum compensation, the distribution relation of the target energy in the space is restored, and the measurement precision of the three-coordinate radar is improved. As shown in FIG. 4, the abscissa is the number of distance units, the ordinate is the elevation value, and the measurement result of the elevation angle is simulated when the weak target flies across the space above the strong ground object at the same elevation angle, so that it can be seen that the traditional moving target algorithm has jump in the elevation angle when the weak target crosses the ground object due to the influence of the ground objectAnd moreover, by adopting the algorithm, when the weak target passes through the ground object, the energy of the ground object has no influence on the elevation angle measurement.
Claims (3)
1. A three-coordinate radar moving target processing method based on clutter frequency spectrum compensation technology is characterized in that:
step 1: let x be ═ x1 x2...xn]Windowing X for a time sequence vector of related pulses of the same distance unit of a certain elevation angle layer of the radar, and performing N-point DFT on windowed data to obtain an N-point DFT result X' (K), wherein K belongs to [ 12.. n.. N ]](ii) a Taking an absolute value of X' (K) to obtain X (K); finding the maximum X (l) of X (K) and the spectral width σ around X (l)wEnergy lines in the range, denoted as [ X (l- σ) ]w/2)...X(l)...X(l+σw/2)]，σwThe clutter division type setting can be adopted;
step 2: for [ X (l-sigma) ]w/2)...X(l)...X(l+σw/2)]Calculating the maximum value X (l) for the frequency value Fk by means of a weighting algorithm0According to Fk0And X (l), calculating an Fk under ideal conditions0DFT spectrum of N after windowing of complex signal with frequency and intensity of X (l)
Mixing X (K) with
Subtracting to obtain Doppler spectrum compensated spectrum Xc(K)；
And step 3: mixing Xc(K) Dividing the Doppler signals into high, medium and low 5 areas according to the Doppler velocity and different Doppler directions, calculating the average value of spectral lines of the 5 areas, and taking the minimum average value as a noise level;
and 4, step 4: let the frequency spectrum of the mth iteration be denoted as Xcm(K) The maximum in the spectrum is denoted Xcm(l'), if Xcm(l') greater than 2 times the noise level, and calculating the maximum value X by a maximum-near spectral line weighting algorithmcm(l') for frequency value Fk1(m) according to Fk1(m) and Xcm(l') calculation under ideal conditionsA Fk1(m) frequency, intensity Xcm(l') DFT spectrum of N after complex signal windowing
Mixing Xcm(K) And
subtracting to obtain Doppler spectrum compensated spectrum Xcm+1(K) (ii) a Repeating the step 4 until Xcm(l') less than 2 times the noise level;
and 5: adopting the common unit average constant false alarm processing on the distance of X (K), if the current distance unit Fk calculated in the step 20The corresponding Doppler channel is over-constant false alarm threshold, and Fk is used0If the speed is larger than the preset speed threshold, selecting Fk of the step 20And X (l) as output; otherwise, if Fk of step 41(m) the corresponding Doppler channel crosses the constant false alarm threshold, and Fk1(m) greater than a predetermined speed threshold output Xcm(l'), otherwise, outputting the noise level calculated in the step 3; and finally, calculating elevation values of the same distance unit data of different elevation layers according to a conventional method.
2. The clutter spectrum compensation technique based three-coordinate radar moving target processing method according to claim 1, wherein: the first weighting spectrum width sigma used in the step 1wA clutter-type setting may be adopted, which may be set according to the doppler channel region where the maximum value x (l) of x (k) is located, and if the doppler channel where x (l) is located is near zero velocity, it may be considered as clutter, the weighted spectral width is set to 1 or 2, and if the doppler channel where x (l) is located is not near zero velocity, it may be considered as clutter, and the weighted spectral width may be set to 3 or 4.
3. The clutter spectrum compensation technique based three-coordinate radar moving target processing method according to claim 1, wherein: in the step 2, an Fk under ideal conditions is calculated0Frequency, intensity X (l)DFT spectrum of N after complex signal windowing
By adopting a direct calculation mode, the method has the advantages that,
windowed N DFT spectrum
Wherein
w (n) is a window function; wherein X (K) and
and subtracting to realize Doppler spectrum compensation.
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