CN106896358A - A kind of high-speed target phase-coherent accumulation detection method based on position rotation transformation - Google Patents
A kind of high-speed target phase-coherent accumulation detection method based on position rotation transformation Download PDFInfo
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- 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
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Abstract
The invention discloses a kind of high-speed target phase-coherent accumulation detection method based on position rotation transformation, belong to radar Technique of Weak Signal Detection field, its feature is to comprise the following steps：First, using radar emission linear FM signal, the echo-signal of the target to receiving carries out pulse compression.Again by the anglec of rotation and estimating speed of position rotation transformation traversal search pulse compression back echo Data Position, all echo data positions are carried out integral-rotation to correct single order range walk using the anglec of rotation of search.Finally, the correlative accumulation of target energy is realized by Fast Fourier Transform (FFT), and target detection is carried out with the peak value of accumulation.The present invention carries out correlative accumulation using the echo amplitude and phase information of moving-target, radar return signal to noise ratio is effectively improved, so as to improve detection performance of the radar to target.Because all operations of the present invention are realized using Fast Fourier Transform (FFT), be conducive to Project Realization, with promotion and application value.
Description
Technical field
The invention belongs to Radar Technology field, it is related to high-speed target detection technique, it is specifically a kind of based on position rotation
The high-speed target phase-coherent accumulation detection method that transformation is changed, can be used for the detections of radar treatment of complex environment high speed weak target.
Background technology
In recent years, with the development of science and technology, especially high-speed flight technology is continued to develop and Modern Stealth Technique
It is increasingly mature, how accurately and efficiently to realize the detection of high-speed target becomes the problem of radar signal processing field.Pass
The solution of system be using preferred radar transmitter frequency, the noise coefficient for improving emitter transmission power, reducing receiver,
Increase antenna aperature etc. changes the measure of radar system parameters.However, these methods are often limited by Project Realization, show
Writing ground increases system development cost.In order to improve detections of radar high speed weak on the premise of radar system basic parameter is not changed
The ability of target, increasing observation and integration time becomes one of effective method.
According to whether phase information, radar target long time integration method can be largely classified into two kinds：Non- coherent product
Tired and correlative accumulation.A kind of typical non-inherent accumulation is Hough transform, and it is accumulated according to the position of target, can
Suppress false-alarm and improve detection performance.Due to phase information, the gain meeting of non-inherent accumulation in low signal-to-noise ratio environment is not used
Substantially reduce.
Correlative accumulation mainly includes moving-target detection (MTD) technology, Keystone conversion and Radon Fourier transformations.MTD
Interference and accumulation energy of the technology using the Doppler filter group strong background clutter of reduction, but the serious distance of high-speed target is walked
Dynamic effect can cause the failure of this method.In order to the linear range for correcting target is walked about, in Keystone conversion and Fu Radon
Leaf transformation is suggested and is applied to radar dim target detection field.Standard K eystone conversion is general to be realized using interpolation arithmetic
To the change of scale of 2-D data plane, so as to eliminate linear range walk about.But in the case where target velocity is very high, it is this
Method often occurs doppler ambiguity effect and there is interpolation accumulation loss.Radon Fourier transformations need by distance and
The two-dimentional Syndicating search of speed carries out correlative accumulation to target energy, calculates increasingly complex.
Generally speaking, the existing method for solving the problems, such as first-order linear range walk mainly passes through interpolation arithmetic or various dimensions
Parameter search is operated, and computing and realization are complicated and there is interpolation loss.Therefore needing badly can simply and effectively correct linear range
The correlative accumulation method walked about.
The content of the invention
The purpose of the present invention is the range walk effect caused by elimination targeted cache degree and estimates target velocity, in low letter
Make an uproar and the correlative accumulation of target energy is realized than in the case of.
Solution of the invention is a kind of high-speed target correlative accumulation detection based on position rotation transformation of research and design
Method, the method comprises the following steps：
Step 1：Echo impulse compresses：
1-1) use radar emission linear FM signal s (tm,tn), wherein tmWhen=mT (m=0,1 ..., M-1) is slow
Between, i.e., the time required to m-th pulse；The fast time, i.e., corresponding to n-th range cell when
Between；T is pulse recurrence interval, fs=kB is sample frequency, and B is signal bandwidth, and k is bandwidth multiple；M represents total number, N
Represent total range cell number.In field of radar, a pulse is referred to as the fast time from the time being transmitted into used by reception, also often
Target range is represented for correspondence；The slow time is made up of a series of pulses, the time needed for representing multiple pulses.
1-2) target echo signal that will be received is designated as sr(tm,tn), and to sr(tm,tn) process of pulse-compression is done, will
Signal after pulse compression is designated as sc(tm,tn), by sc(tm,tn) in slow time tmWith fast time tnRespectively according toAnd n
=fstnSubstitution of variable is carried out, the echo data s in m-n domains is obtainedc(m,n)。
Step 2：Setting anglec of rotation hunting zone is：
Set angle hunting zone is [θmin,θmax], wherein θminIt is the lower bound of angle searching scope；θmaxIt is angle searching
The upper bound of scope, and its angle searching is set at intervals of Δ θ.
Step 3：The search anglec of rotation：
3-1) to angle of aspect θ in [θmin,θmax] in scan for, travel through each angle of aspect with intervals of Δ θ, often select
One angle of aspect θ just can obtain a corresponding spin matrix, and spin matrix expression is
3-2) the echo-signal s after the spin matrix that will be obtained every time and substitution of variablecThe position of each data in (m, n)
Put coordinate multiplication.To echo-signal sc(m, n) carries out rotation and moves, echo data matrix s new after being rotatedc(m′,n′；
θ), wherein (m, n) is echo-signal scThe position coordinates of arbitrary data in (m, n), (m ', n ') is (m, n) postrotational position
Coordinate, its position rotation transformation relation is：
3-3) the echo data matrix s to being obtained after rotation every timec(m′,n′；θ), with m ' for variable is FFT (quick Fu
In leaf transformation) accumulated after take the peak value of accumulation, travel through all angles of aspect and simultaneously find the corresponding accumulation peak value of each angle of aspect.
Compare the maximum angle of aspect θ as angle of aspect estimates accumulated corresponding to peak value after all accumulation peak values, be designated as
I.e.
Wherein,Represent with m ' as variable does Fast Fourier Transform (FFT)；| | represent modulo operation.
Expression takes the θ corresponding to maximum.
Step 4：Estimate target velocity：
According to the relation between angle of aspect and speedUsing angle of aspect estimateCan obtain speed
EstimateWherein c is the light velocity.
Step 5：Target detection：
By angle of aspect estimateSubstitute into sc(m′,n′；θ), you can eliminate linear range walk about item and after correct time
Ripple data matrix, is designated as scorr(m ', n '), now backward energy fall in same range cell.
By scorr(m ', n ') can obtain coherent integration result with m' as variable is FFT, be designated as sint(fm',n′)；Wherein,
fm'It is the corresponding frequency domain variables of m '；Peak value in coherent integration result compares with threshold value, more than target presence is then thought, otherwise
Think no target.
Beneficial effects of the present invention：The present invention is detected to target using the method for pulse accumulation, can effectively pressed down
Noise processed, while being walked about with the linear range that position rotation transformation corrects target, can improve the signal to noise ratio and radar of echo
Detection performance.Moreover, it is an advantage of the present invention to because all operations of the present invention are realized using Fast Fourier Transform (FFT), be beneficial to
Project Realization, with promotion and application value.
Brief description of the drawings
Fig. 1 is the FB(flow block) of the method provided by the present invention；
Fig. 2 represents the result after the target echo pulse compression that radar is received；
Fig. 3 represents anglec of rotation Search Results of the invention；
Fig. 4 represents target velocity estimated result of the invention；
Fig. 5 is represented and is used the Range Walk Correction result after the present invention search anglec of rotation；
Fig. 6 is represented using coherent integration result of the invention.
Specific embodiment
To make the object, technical solutions and advantages of the present invention clearer, with reference to implementation method and accompanying drawing, to this hair
It is bright to be described in further detail.
The main method using emulation experiment of the invention is verified that all steps, conclusion are all in computational science software
Its correctness is verified on Matlab R2014a.Specific implementation of the invention is given with reference to Fig. 1：
Step 1：Echo impulse compresses：Believed to single target transmitting linear frequency modulation using Matlab R2014a emulation radars
Number and obtain echo data sr(tm,tn), by sr(tm,tn) carry out pulse compression and obtain sc(tm,tn), wherein tm=mT (m=0,
1 ..., M-1) it is slow time, i.e., m-th pulse required time；Fast time, i.e., n-th away from
From the time corresponding to unit；T is pulse recurrence interval, numerically equal to the inverse of pulse recurrence frequency；fs=kB is sampling
Frequency, B is signal bandwidth, and k is bandwidth multiple；M represents total number, and N represents total range cell number.Sets target and thunder
Up in tmThe distance at moment is：
r(tm)=r0+vtm
Wherein, r0=300km is that target is 300km relative to the initial distance of radar, and v=2000m/s is to represent target
Radial velocity is 2000m/s, and radar emission signal carrier frequency is 1.5GHz, and signal bandwidth is 5MHz, and sample frequency is 10MHz, thunder
The pulse recurrence frequency for reaching is 500Hz, and the umber of pulse included in a correlative accumulation time is 256, and signal to noise ratio is -12dB.
By sc(tm,tn) in slow time tmWith fast time tnRespectively according toAnd n=fstnSubstitution of variable is carried out to obtain
sc(m,n).As shown in Fig. 2 due to the high-speed motion of target, backward energy is dispersed in different distance lists in the correlative accumulation time
In first, that is, there occurs range walk.
Step 2：Anglec of rotation hunting zone is set：Set angle hunting zone is [θmin,θmax], wherein θminIt is that angle is searched
The lower bound of rope scope；θmaxIt is the upper bound of angle searching scope, and its angle searching is set at intervals of Δ θ.
Step 3：The search anglec of rotation：
To angle search value θ in [θmin,θmax] in scan for, travel through each search value with intervals of Δ θ, often select
One search value θ just can obtain a corresponding spin matrixThe spin matrix that to obtain every time with
Echo-signal s after substitution of variablecThe position coordinates (m, n) of each data is multiplied in (m, n), and each postrotational position is
(m ', n '), its position rotation transformation can be expressed as：
Echo data matrix new after rotation is designated as sc(m′,n′；θ).To the echo data square obtained after rotation every time
Battle array sc(m′,n′；θ) with m ' for variable does the peak value that accumulation is taken after FFT is accumulated, travel through all angles of aspect and find each and search
The corresponding accumulation peak value in rope angle.Compare and angle as angle of aspect corresponding to maximum accumulation peak value is found after all accumulation peak values
Estimate, is designated asFig. 3 is anglec of rotation Search Results, wherein, ordinate (Y-axis i.e. in figure) is exactly to represent accumulation amplitude,
Each one accumulation result of search angle correspondence, correspondence at peakIts expression is：
Wherein,Represent with m ' as variable does Fast Fourier Transform (FFT)；| | represent modulo operation；
Expression takes the θ corresponding to maximum.
Step 4：Estimate target velocity：
According to the relation between angle of aspect and speed, using angle of aspect estimateCan obtain the estimate of speedFigure
4 is velocity estimation result, and ordinate still represents accumulation amplitude, one accumulation result of each speed correspondence, the peak value position of curve
Put and be exactlyThe expression of relation is as follows between angle of aspect and speed：
Wherein, c is the light velocity.
Step 5：Target detection：
By angle of aspect estimateSubstitute into sc(m′,n′；θ), you can eliminate linear range walk about item and after correct time
Ripple data matrix scorr(m ', n '), as shown in figure 5, range walk is corrected, now backward energy falls in same range cell
It is interior.By scorr(m ', n ') can obtain coherent integration result with m ' for variable is FFT, be designated as sint(fm',n′)；Wherein, fm'It is
The corresponding frequency domain variables of m '.As shown in fig. 6, when the peak value in coherent integration result is then thought to detect target more than threshold value.
In sum, this method detected using the method for multi-pulse accumulation to target, can be effectively eliminated linear
Range walk effect simultaneously estimates target velocity, realizes the correlative accumulation and target detection of high-speed target backward energy, effectively carries
The signal to noise ratio of radar return high and the detectability to high-speed target.
Claims (1)
1. a kind of high-speed target phase-coherent accumulation detection method based on position rotation transformation, it is characterized in that comprising the following steps：
Step 1：Echo impulse compresses：
1-1) use radar emission linear FM signal s (tm,tn), wherein tm=mT represents the slow time of m-th pulse, and T is represented
Pulse recurrence interval；Represent the n-th fast time of range cell, fs=kB is sample frequency, and B is signal bandwidth, and k is
Bandwidth multiple；
1-2) target echo signal that will be received is designated as sr(tm,tn), to target echo signal sr(tm,tn) do at pulse compression
Reason, s is designated as by the signal after pulse compressionc(tm,tn), by sc(tm,tn) in slow time tmWith fast time tnRespectively according toAnd n=fstnSubstitution of variable is carried out, the echo data s in m-n domains is obtainedc(m,n)；
Step 2：It is [θ to set anglec of rotation hunting zonemin,θmax], wherein θminIt is the lower bound of angle searching scope；θmaxIt is angle
The upper bound of hunting zone, and its angle searching is set at intervals of Δ θ；
Step 3：The search anglec of rotation：
3-1) to angle of aspect θ in [θmin,θmax] in scan for, travel through each angle of aspect θ with intervals of Δ θ, useExpression corresponds to the spin matrix of each angle of aspect θ；
3-2) the echo-signal s after the spin matrix that will be obtained every time and substitution of variablecThe position of each data is sat in (m, n)
Mark is multiplied (m, n), obtains postrotational position coordinates (m ', n '), and the position rotation transformation based on (m ', n ') Yu (m, n) is obtained
sc(m, n) postrotational echo data matrix sc(m′,n′；θ)；
Wherein described position rotation transformation is
3-3) the echo data matrix s to being obtained after rotation every timec(m′,n′；After θ) doing Fast Fourier Transform (FFT) for variable with m '
Draw accumulation fund peak value, travel through all angles of aspect and simultaneously find the corresponding accumulation peak value of each angle of aspect；By in all accumulation peak values
Angle of aspect corresponding to maximum accumulation peak value is used as angle of aspect estimate
Step 4：Estimate target velocity：
According to formulaObtain velocity estimation valueWherein c is the light velocity；
Step 5：Target detection：
By angle of aspect estimateSubstitute into sc(m′,n′；θ), s is obtainedcorr(m′,n′)；
By scorr(m ', n ') for variable does Fast Fourier Transform (FFT), obtains coherent integration result with m ', is designated as sint(fm',n′)；
Wherein, fm'It is the corresponding frequency domain variables of m '；
Coherent integration result sint(fm', n ') peak value compare with predetermined threshold value, if more than if think target exist, otherwise recognize
It is no target.
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| CN107329138A (en) * | 2017-08-07 | 2017-11-07 | 电子科技大学 | A kind of PD distance by radars, which are walked about, to be corrected and phase-coherent accumulation detection method |
| CN107561508A (en) * | 2017-08-24 | 2018-01-09 | 电子科技大学 | A kind of phase-coherent accumulation detection method for even accelerated motional objects |
| CN108196241A (en) * | 2018-02-07 | 2018-06-22 | 北京航空航天大学 | A kind of High-speed target speed estimation method based on Hough transform |
| CN108549066A (en) * | 2018-07-27 | 2018-09-18 | 电子科技大学 | A kind of wideband radar high-speed target integration detection method based on scale RFT |
| CN109073743A (en) * | 2017-12-18 | 2018-12-21 | 深圳市大疆创新科技有限公司 | Weak target detection method, microwave radar sensor and unmanned plane |
| CN109884621A (en) * | 2019-02-28 | 2019-06-14 | 上海交通大学 | Echo in Radar Altitude Meter correlative accumulation method |
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