CN107561508A - A kind of phase-coherent accumulation detection method for even accelerated motional objects - Google Patents
A kind of phase-coherent accumulation detection method for even accelerated motional objects Download PDFInfo
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Abstract
The invention discloses a kind of phase-coherent accumulation detection method for even accelerated motional objects, belong to Radar Technology field.Then the present invention carries out pulse compression first with PD radar emission linear FM signals to the echo-signal containing target received.Coordinate is carried out to the echo-signal after pulse compression again and moves conversion to correct the range walk of target.Then, the Doppler for target being eliminated using Fourier Transform of Fractional Order is walked about and realizes the correlative accumulation of energy.It because the present invention carries out long-time phase-coherent accumulation using the amplitude in target echo and phase information simultaneously, therefore can effectively suppress noise, improve detection performance of the radar to weak target.It in addition, the Fourier Transform of Fractional Order of the present invention can be realized by Fast Fourier Transform (FFT), therefore can greatly reduce operand, be advantageous to quick detection of the radar to weak target.
Description
Technical field
The invention belongs to the Detection for Moving Target in Radar Technology field, and in particular to one kind is used for uniformly accelerated motion mesh
Target phase-coherent accumulation detection method.
Background technology
In recent years, how rapidly and efficiently to realize and mesh is moved to low signal-to-noise ratio with progress with the development of science and technology
Mark rapidly and effectively detection become in radar signal processing field one it is challenging the problem of.Due to distant object
Very low echo signal to noise ratio is usually constructed with low radar cross section target, therefore this two classification is often nominally faint mesh by us
Mark.In order to effectively detect weak target, increase echo accumulation number and to extend integration time be a kind of effective method.
However, with the extension of integration time, target inevitably appearance distance can walk about and be walked about with Doppler.Therefore, distance is walked
The dynamic Detection results that weak target is determined with the compensation effect that Doppler walks about.
At present, radar target long time integration method can be largely classified into non-inherent accumulation and the class of correlative accumulation two.
Non-inherent accumulation only considers the amplitude information of echo data, and implementation is relatively simple.However, due to its phase letter is not used
Breath, accumulation gain of such method in low signal-to-noise ratio environment can greatly reduce.Correlative accumulation then considers echo data simultaneously
Amplitude and phase information, in-phase stacking specifically is carried out to echo, therefore higher accumulation gain can be obtained.
Traditional correlative accumulation method such as moving-target detection (MTD) technology can to residence time in a range cell or
Moving target in doppler cells is accumulated and detected.When target appearance distance is walked about, that is, there is target across multiple distances
During unit, traditional accumulation method MTD will fail.The methods of Keystone conversion, AR-MTD algorithms, Radon Fourier transformations
Can correction distance walk about, realize uniform motion target energy accumulation, detection.It is however, increasingly complex for motion mode
Uniformly accelerated motion, it occurs that target across the multiple range cells and multiple Doppler's resolution cells the problem of, i.e., is sent out simultaneously simultaneously
Raw range walk and Doppler walk about.Doppler walks about when can cause accumulation energy in the scattered of frequency domain, can lose the above method
Effect.
Walked about to solve range walk and Doppler, a variety of methods are suggested.Two step second order Keystone conversion passes through weight
Multiple interpolation carries out the correction of range walk and the accumulation of energy, however, a large amount of interpolation losses, and multiple interpolation be present in this method,
Process complexity is cumbersome.Generalized Radon Fourier transformation can eliminate range walk and Doppler walks about, by distance, speed and
The three-dimensional Syndicating search of acceleration carries out correlative accumulation to target energy.However, the calculating of generalized Radon Fourier transformation is very
Complexity, influence the real-time of Radar Signal Processing.All in all, existing method is mainly searched by interpolation arithmetic or various dimensions parameter
Rope realizes that operand is bigger, implementation is more complicated makes the reduction of its practicality.
The content of the invention
The goal of the invention of the present invention is：For above-mentioned problem, there is provided one kind can correct even accelerated motional objects
Range walk and Doppler walk about effect, and realize that the correlative accumulation of target energy and target are examined in low signal-to-noise ratio environment
Survey.
The phase-coherent accumulation detection method for even accelerated motional objects of the present invention, comprises the following steps：
Step 1：Using PD (pulse Doppler) radar emission linear FM signal, z is designated ast(τ,tn), radar is received
Target echo signal be designated as zr(τ,tn).Wherein, τ is the fast time, i.e., from be transmitted into receive individual pulse used in time (
It can be used to corresponding expression target range)；tnRepresent slow time, i.e. n-th of pulse signal required time, i.e. tn=nT (n=
1 ..., N), T and N represent pulse recurrence interval and the overall pulse number launched respectively.
Initial distance s based on radar to target0, target radial speed v and radial acceleration a can obtain target and radar
In tnThe distance at moment is：
Step 2：Process of pulse-compression is carried out to echo-signal, pulse pressure echo-signal is obtained, is designated as zc(τ,tn).Again to arteries and veins
Press echo-signal zc(τ,tn) in fast time τ, slow time tnDiscrete processes are carried out, obtain the fast time m after discrete processes, slow
Time n, z is designated as so as to obtain the echo-signal after discrete processes in m-n domainsc(m, n), wherein m=fsτ、fsIt is sampling
Frequency.
Step 3：Step-size in search Δ σ based on setting carries out traversal search, profit in angle searching scope to angle variables
Substitution of variable is carried out with the translation-angle σ searched every time (to carry out coordinate to m, n and move conversion, thus translation-angle σ also may be used
Angle is moved in expression, and one is moved the corresponding target velocity in angle, i.e., the search for moving angle is searched equivalent to target velocity
Rope), obtain coordinate and move fast time m ', slow time n ' after conversion, the echo-signal moved so as to obtain coordinate after conversion is
zc(m′,n′；σ), wherein coordinate moves transformation for mula and is：
And the echo-signal z after conversion replacement is moved to each coordinatec(m′,n′；σ) Fourier Transform of Fractional Order is done to go forward side by side
Row amplitude is accumulated, and translation-angle σ corresponding to maximum accumulation amplitude as the estimate of angle variables, is designated asI.e.Wherein FRFT () represents to do fractional order Fast Fourier Transform (FFT)；| | expression takes
Modulo operation；Represent σ corresponding when the object in bracket takes maximum.
Step 4：Judge current estimateWhether in default error range (the value model for accuracy judgement is preset
Enclose), if it is not, then adjustment step-size in search Δ σ continues executing with step 3；If, then it represents that angle variables estimation is accurate, will work as anterior angle
Spend variable estimateEcho-signal is substituted into, the correction walked about of completing to adjust the distance willAs range walk quilt
The echo-signal of correction, whereinIn order to simplify description, the echo-signal after note correction is designated as zc(m′,
n′).After Range Walk Correction, all echoes are located atIn range cell, wherein,Represent initial to target with radar
Distance s0Corresponding range cell.By range cellIn echo-signal be designated as zc(n′).To zc(n ') is fractional order Fu
In leaf transformation can eliminate Doppler and walk about, carry out the correlative accumulation of energy.
Step 5：To the peak value after correlative accumulation compared with predetermined threshold value, when accumulation peak value is higher than threshold value,
Represent that target can be detected；Otherwise target can not be detected.
The formula of Fourier Transform of Fractional Order in the step 4 is：
Wherein, Fp() represents to do Fourier Transform of Fractional Order operation by variable of p；The anglec of rotation is represented, α is
Convert exponent number；Kp(n ', u) represents transformation kernel.
The present invention is first with PD radar emission linear FM signals, the then echo-signal containing target to receiving
Carry out pulse compression.Substitution of variable is carried out to the echo-signal after pulse compression to correct the range walk of target again.Then, it is sharp
The Doppler that target is eliminated with Fourier Transform of Fractional Order walks about and realizes the correlative accumulation of energy.
In summary, by adopting the above-described technical solution, the beneficial effects of the invention are as follows：Simultaneously using in target echo
Amplitude and phase information carry out long-time phase-coherent accumulation, can effectively suppress noise, improve radar to uniformly accelerated motion mesh
Target detectability.In addition, the Fourier Transform of Fractional Order of the present invention can be realized by Fast Fourier Transform (FFT), therefore can be with
Greatly reduce operand, be advantageous to quick detection of the radar to weak target.
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 of target echo pulse compression；
Fig. 3 represents the Range Walk Correction result using the present invention；
Fig. 4 represents the coherent integration result using the present invention.
Embodiment
To make the object, technical solutions and advantages of the present invention clearer, with reference to embodiment and accompanying drawing, to this hair
It is bright to be described in further detail.
It is of the invention mainly to be verified that all steps and conclusion are all to use computational science software using the method for emulation experiment
Matlab R2014a verify its correctness.The number of sets target is 1, and target is 300km with respect to the initial distance of radar,
Target radial speed is 2500m/s, and target radial acceleration is 24m/s2, radar emission carrier frequency is 0.3GHz, and radar band is a width of
5MHz, radar pulse repetition frequency 500Hz, overall pulse number is 512 in the correlative accumulation time, and signal to noise ratio is -10dB.Tie below
Close the specific implementation that Fig. 1 provides the present invention：
Step 1：Z is designated as using PD radar emission linear FM signalst(τ,tn), the target echo that radar is received is believed
Number it is designated as zr(τ,tn).Wherein, τ represents the fast time；tnRepresent the slow time；
Sets target is with radar in tnThe distance at moment is：Wherein, s0, v and a be respectively thunder
Reach initial distance, target radial speed and the radial acceleration of target.
Step 2：Process of pulse-compression is carried out to echo-signal, the signal after pulse pressure is obtained and is designated as zc(τ,tn).Fig. 2 shows,
The serious range walk that target echo occurs after pulse pressure.Afterwards, to pulse pressure back echo signal zc(τ,tn) in variable τ and
tnDiscrete processes are carried out, i.e.,Wherein, fsIt is sample frequency.In the echo-signal in m-n domains after discrete processes
It is designated as zc(m,n)。
Step 3：In hunting zone [σmin,σmax] in traversal is carried out to angle variables σ as the scouting interval using Δ σ searched
Rope, wherein, σminIt is the lower bound of hunting zone, σmaxRepresent its upper bound.(will be every time using the translation-angle searched every time
Search result is assigned to angle variables σ) substitution of variable is carried out, remember that the echo-signal after substitution of variable is zc(m′,n′；σ), wherein
For m ' to move rear new fast time variable, n ' is to move rear new slow time variable.The echo after replacement is moved to each coordinate
Signal zc(m′,n′；σ) do Fourier Transform of Fractional Order to be accumulated and compare amplitude, corresponding to maximum accumulation amplitude is
The estimate of angle variables, is designated as
Step 4：Judge current estimateWhether in default error range, continue if it is not, then adjusting step-size in search Δ σ
Perform step 3；If, then it represents that angle variables estimation is accurate, willThe echo letter being corrected as range walk
Number, in order to simplify description, the echo-signal after note correction is designated as zc(m′,n′).As shown in figure 3, move replacement, mesh by coordinate
Subject distance, which is walked about, to be corrected.After Range Walk Correction, all echoes are located atIn range cell, wherein,It is and thunder
Reach target initial distance s0Corresponding range cell.By range cellIn echo-signal be designated as zc(n′).To zc
(n '), which does Fourier Transform of Fractional Order and can eliminate Doppler, to walk about, and carries out the coherent product of the accumulation and focusing of energy, i.e. energy
It is tired.As Fig. 4 shows the coherent integration result of target energy.
Step 5：To the peak value after correlative accumulation compared with predetermined threshold value, when accumulation peak value is higher than threshold value,
Represent that target can be detected；Otherwise target can not be detected.
Claims (2)
1. a kind of phase-coherent accumulation detection method for even accelerated motional objects, it is characterised in that comprise the following steps：
Step 1：Using pulse Doppler radar transmitting linear FM signal and receives echo-signal, transmission signal is designated as zt(τ,
tn), the target echo signal received is designated as zr(τ,tn), wherein τ represents the fast time；tnRepresent the slow time；
Step 2：To echo-signal zr(τ,tn) process of pulse-compression is carried out, pulse pressure echo-signal is obtained, is designated as zc(τ,tn)；
Again to pulse pressure echo-signal zc(τ,tn) in fast time τ, slow time tnDiscrete processes are carried out, after obtaining discrete processes
Fast time m, slow time n, z is designated as so as to obtain the echo-signal after discrete processes in m-n domainsc(m, n), wherein m=fsτ、fsIt is sample frequency, T is pulse recurrence interval；
Step 3：Step-size in search Δ σ based on setting carries out traversal search in angle searching scope to angle variables, using every
The secondary translation-angle σ searched to fast time m, slow time n carry out coordinate move conversion, obtain coordinate move convert after it is fast when
Between m ', slow time n ', so as to obtain coordinate move conversion after echo-signal be zc(m′,n′；σ), wherein coordinate moves conversion
Formula is：
And the echo-signal z after conversion replacement is moved to each coordinatec(m′,n′；σ) do Fourier Transform of Fractional Order and carry out width
Value accumulation, translation-angle σ corresponding to maximum accumulation amplitude as the estimate of angle variables, is designated as
Step 4：Judge current estimateWhether in default error range, if it is not, then adjustment step-size in search Δ σ is continued executing with
Step 3；If so, then by current angular variable estimateSubstitute into echo-signal zc(m′,n′；σ), adjust the distance to walk about and be corrected,
And the echo-signal after correction is designated as zc(m′,n′)；
By echo-signal zcEcho-signal in the range cell corresponding fast time m ' of (m ', n ') is designated as zc(n '), and to returning
Ripple signal zcAfter (n ') does Fourier Transform of Fractional Order, the correlative accumulation of energy is carried out；
Step 5：To the peak value after correlative accumulation compared with predetermined threshold value, when accumulation peak value is higher than threshold value, represent
Target can be detected；Otherwise target can not be detected.
2. the method as described in claim 1, it is characterised in that the formula of the Fourier Transform of Fractional Order in the step 4 is：
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Wherein, Fp() represents to do Fourier Transform of Fractional Order operation by variable of p；The anglec of rotation is represented, α is conversion
Exponent number；Kp(n ', u) represents transformation kernel.
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| 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 |
| CN108549067A (en) * | 2018-07-27 | 2018-09-18 | 电子科技大学 | A kind of phase-coherent accumulation detection method being applied to three rank maneuvering targets |
| CN108919221A (en) * | 2018-07-17 | 2018-11-30 | 武汉大学 | A kind of phase-coherent accumulation detection method for variable accelerated motion target |
| CN108919222A (en) * | 2018-07-17 | 2018-11-30 | 武汉大学 | A kind of phase-coherent accumulation detection method for even accelerated motional objects |
| CN109324322A (en) * | 2018-10-31 | 2019-02-12 | 中国运载火箭技术研究院 | A kind of direction finding and target identification method based on passive phased array antenna |
| CN109375206A (en) * | 2018-09-19 | 2019-02-22 | 北京遥感设备研究所 | A kind of moving target speed-measuring method based on speed search |
| CN109613507A (en) * | 2018-12-21 | 2019-04-12 | 北京理工大学 | A kind of detection method for high-order maneuvering target radar return |
| CN111123214A (en) * | 2019-12-18 | 2020-05-08 | 南京理工大学 | High-speed high-mobility target detection method based on polynomial rotation-polynomial Fourier transform |
| CN112255609A (en) * | 2020-10-14 | 2021-01-22 | 哈尔滨工业大学 | Constant-acceleration maneuvering target coherent accumulation detection method |
| CN112363120A (en) * | 2020-11-03 | 2021-02-12 | 中国人民解放军海军航空大学 | Frequency shift interference identification method based on two-dimensional fractional Fourier transform |
| CN113030895A (en) * | 2021-03-10 | 2021-06-25 | 电子科技大学 | Multi-frame coherent accumulation detection method for weak target |
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| CN108919222A (en) * | 2018-07-17 | 2018-11-30 | 武汉大学 | A kind of phase-coherent accumulation detection method for even accelerated motional objects |
| CN108549067A (en) * | 2018-07-27 | 2018-09-18 | 电子科技大学 | A kind of phase-coherent accumulation detection method being applied to three rank maneuvering targets |
| CN108549067B (en) * | 2018-07-27 | 2020-06-02 | 电子科技大学 | Coherent accumulation detection method applied to third-order maneuvering target |
| 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 |
| CN109375206A (en) * | 2018-09-19 | 2019-02-22 | 北京遥感设备研究所 | A kind of moving target speed-measuring method based on speed search |
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| CN109613507B (en) * | 2018-12-21 | 2021-04-06 | 北京理工大学 | Detection method for high-order maneuvering target radar echo |
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| CN111123214A (en) * | 2019-12-18 | 2020-05-08 | 南京理工大学 | High-speed high-mobility target detection method based on polynomial rotation-polynomial Fourier transform |
| CN112255609A (en) * | 2020-10-14 | 2021-01-22 | 哈尔滨工业大学 | Constant-acceleration maneuvering target coherent accumulation detection method |
| CN112363120A (en) * | 2020-11-03 | 2021-02-12 | 中国人民解放军海军航空大学 | Frequency shift interference identification method based on two-dimensional fractional Fourier transform |
| CN112363120B (en) * | 2020-11-03 | 2022-10-25 | 中国人民解放军海军航空大学 | Frequency shift interference identification method based on two-dimensional fractional Fourier transform |
| CN113030895B (en) * | 2021-03-10 | 2022-07-15 | 电子科技大学 | Multi-frame coherent accumulation detection method for weak target |
| CN113030895A (en) * | 2021-03-10 | 2021-06-25 | 电子科技大学 | Multi-frame coherent accumulation detection method for weak target |
| CN113406592A (en) * | 2021-06-15 | 2021-09-17 | 哈尔滨工业大学 | High-frequency ground wave radar weak target accumulation detection method and computing device |
| CN113406592B (en) * | 2021-06-15 | 2022-06-10 | 哈尔滨工业大学 | High-frequency ground wave radar weak target accumulation detection method and computing device |
| CN113687340A (en) * | 2021-08-24 | 2021-11-23 | 重庆交通大学 | Millimeter wave radar-based remote moving target detection method |
| CN113687340B (en) * | 2021-08-24 | 2024-02-23 | 重庆交通大学 | Long-distance moving target detection method based on millimeter wave radar |
| CN114371460A (en) * | 2022-01-24 | 2022-04-19 | 电子科技大学 | Airborne radar sea surface moving target energy accumulation and sea clutter suppression method |
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| CN115902784B (en) * | 2022-12-12 | 2023-09-08 | 电子科技大学 | Uniform acceleration motion ultra-high-speed target accumulation detection method for large-time wide-bandwidth product radar |
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