CN113219451B - Target speed estimation method based on sub-aperture radar interference - Google Patents
Target speed estimation method based on sub-aperture radar interference Download PDFInfo
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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
- G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
- G01S13/50—Systems of measurement based on relative movement of target
- G01S13/58—Velocity or trajectory determination systems; Sense-of-movement determination systems
- G01S13/589—Velocity or trajectory determination systems; Sense-of-movement determination systems measuring the velocity vector
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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
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Abstract
The invention discloses a target speed estimation method based on sub-aperture radar interference. The invention can be applied to long-distance, all-weather and macro-scale real-time detection of moving targets such as vehicles, ships and the like, and solves the defects that the synthetic aperture radar image becomes fuzzy and generates position deviation due to Doppler frequency shift generated by moving targets.
Description
Technical Field
The invention belongs to the technical field of radar monitoring, and particularly relates to a target speed estimation method based on sub-aperture radar interference.
Background
With the increasing speed of urban construction, the hazard of surface deformation to human living environment constitutes a potential risk. The surface deformation is mainly divided into transient burst deformation and sustained slow deformation, wherein the transient burst deformation refers to deformation caused by natural factors such as volcanic eruption, mud-rock flow, tsunami, earthquake motion and the like, and the sustained slow deformation
The main causes are ground subsidence caused by large-scale urban engineering construction and excessive groundwater extraction. The ground subsidence has the characteristics of slow cause development, long duration and great control difficulty, and causes great harm to high-speed railways, buildings, infrastructure, life line engineering and the like. Therefore, it is important to continuously monitor the slow deformation such as the ground subsidence for a long period of time.
At present, the common ground surface deformation monitoring method mainly adopts equipment such as a precise level gauge, a range finder, a GPS, a bedrock mark, a layering mark and the like to measure the deformation information of the ground surface based on a single-point or net-laying method, has high monitoring precision, but consumes a large amount of manpower and material resources, and is difficult to develop deformation monitoring in a large scale range. The satellite interference monitoring technology has the advantages of all-weather, wide coverage, repeatable observation, high precision and the like, thereby providing an effective means for high-precision ground surface deformation monitoring. However, radar measures a pitch, so it is not possible to distinguish whether the displacement is from the horizontal or vertical direction, i.e. there is a direction ambiguity. The satellite interference radar measurement only acquires the earth surface deformation component along the radar Sight (Line of Sight, loS), and cannot acquire the three-dimensional deformation (vertical, east-west and north-south deformation) of the real earth surface, namely the earth surface deformation direction of the satellite interference radar is fuzzy, and the defects limit the field of monitoring the three-dimensional deformation of the real earth surface of the satellite interference radar in ground subsidence, landslide, volcanic activity, earthquake and the like.
However, satellite interference radar deformation observation has the inherent disadvantage of direction ambiguity in the range measurement, and the problem of time-space incoherence caused by the interference of systematic errors on the earth surface deformation is easily received, so that a target speed estimation method based on sub-aperture radar interference is provided.
Disclosure of Invention
The invention aims to solve the problems in the prior art and provides a target speed estimation method based on sub-aperture radar interference.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
the invention comprises the following steps:
s1: changing the phases of echo signals according to the moving object, acquiring a plurality of phases of echo signals of the moving object, and the relative speed and the relative distance between the antenna and the moving object, acquiring the echo signals of the moving object, and determining the speed component relation with the object;
the relative distance relation between the antenna and the target object is
Wherein,is a relative distance vector; />For the relative velocity vector of the antenna and the object, +.>For the antenna speed vector, ">Is a target velocity vector;
the relation between the echo signal and the distance vector is that
Wherein A (t) represents the amplitude of the signal, lambda is the wavelength,is a distance vector;
within a sufficiently small time intervalTaylor series (Taylor series) expansion, greater than t 3 Is negligible and +.>Is far greater than the speed
Where a, b is the ratio factor a=v between the antenna speed and the target speed component x /U，b＝v y /U，v x ，v y The velocity components of the velocity of the moving object in the range (range) and azimuth (azimuth) directions are respectively represented,represents the antenna speed, typically |a|, |b| < 1, and is constant.
The mathematical expression of the echo signal of the moving object can be written as the mathematical expression of the bird song pattern
Where y=ut denotes the position of the antenna in the synthetic aperture, the amplitude a (y) is real and does not affect the estimation result, f 0 ，f 1 ，f 2 The initial phasor, the initial frequency, and the rate of change of frequency, respectively.
S2: the echo signal is modularized into a polynomial signal mixed with Gaussian noise, the original aperture of the synthetic aperture radar is divided into a plurality of sub apertures with equal length, and then signals of a plurality of sub apertures are obtained through output;
the synthetic aperture radar echo signal pattern is a discrete signal of a quadratic polynomial and is typically contaminated by noise, given that it is additive noise:
s(y)＝e -jψ(y) +n(y)，y∈(0，Y)
wherein ψ (η) =f 0 +f 1 y+f 2 y 2 Is the phase of the signal, which is in the form of a bird song; y total length of sample; n (y) is gaussian and uncorrelated complex noise.
The data contained in the original aperture is divided into M sub-apertures, each sub-aperture has a data length N, the sub-aperture length is DeltaY=N r, and r is a sampling interval.
The interference phase of the j (j= 0,1,2,3L) th pen is the interference result of the j and j+1 sub-aperture data, and the relation is that
Similarly, the j+1th pen has an interference phase of
The j and j+1 phases are interfered with each other, so that the signal of the sub-aperture is interfered to generate a phase difference containing a second order coefficient
Wherein,the interference phases of the j+1th and j th strokes, respectively, ΔY being the sub-aperture length, +.>Is interference noise, f 2 Is the rate of change of frequency.
S3, generating a phase difference containing a second-order coefficient by interference processing of the signals of the plurality of sub-apertures;
s4: after demodulating an original signal, calculating a first-order Doppler coefficient obtained by estimating the Doppler coefficient and the target speed by the phase difference to obtain an estimated value of the initial frequency;
s5, calculating a slope distance direction speed component through the estimated value of the initial frequency so as to estimate the speed of the moving object with high precision.
The phase difference obtained frequency slope containing second-order coefficient is generated by the interference processing of the signal of the sub-aperture
Averaging to further suppress noise
The interference phase of the j-th penInterference is available
The initial frequency is f 1i .
The result after averaging is
Wherein, the M original aperture data divides the number of sub-aperture data, N each sub-aperture data length,generating phase difference containing second order coefficient for signals of adjacent sub-apertures through interference treatment>Phase difference comprising first order coefficient, which is sub-aperture self-coherence,/->To interfere with noise, the longer the sub-aperture is, the more the estimated result is offset.
Further, the formula of the velocity component of the target in the step S1 is
Wherein the amplitude A (y) is real and its variation does not affect the estimation result; y=ut represents the position of the antenna in the synthetic aperture;is the relative distance between the antenna and the target; a, b are the scaling factors a=v between the antenna speed and the target speed component x /U，b＝v y /U，v x ，v y Representing the velocity component of the velocity of the moving object in the pitch (range) and azimuth (azimuth) directions, respectively,/->Represents the antenna speed, typically |a|, |b| < 1, and is constant; f (f) 0 ，f 1 ，f 2 The initial phasor, the initial frequency, and the rate of change of frequency, respectively.
Further, the calculation formula of the polynomial signal mixed with Gaussian noise is
s(y)＝e -jψ(y) +n(y)，y∈(0，Y)
Wherein ψ (η) =f 0 +f 1 y+f 2 y 2 Is the phase of the signal, which is in the form of a bird song; y total length of sample; n (y) is gaussian and uncorrelated complex noise.
The data contained in the original aperture is divided into M sub-apertures, each sub-aperture has a data length N, the sub-aperture length is DeltaY=N r, and r is a sampling interval.
Mutually interfering the j and j+1 phases to obtain a signal with a sub-aperture, and generating a phase difference containing a second-order coefficient by interference treatment
Wherein,the interference phases of the j+1th and j th strokes, respectively, ΔY being the sub-aperture length, +.>Is interference noise, f 2 Is the rate of change of frequency.
Further, the method for calculating the estimated value of the initial frequency includes:
estimation of rate of change of frequency
Estimate of initial frequency:
wherein, the M original aperture data divides the number of sub-aperture data, N each sub-aperture data length,generating phase difference containing second order coefficient for signals of adjacent sub-apertures through interference treatment>Phase difference comprising first order coefficient, which is sub-aperture self-coherence,/->To avoid the deviation of the estimation result caused by the longer sub-aperture for interference noise, the requirement of +.>
Compared with the prior art, the invention has the beneficial effects that:
the invention divides the original aperture of the synthetic aperture radar into a plurality of sub apertures with the same length, then generates phase difference by the interference processing of the signals of the sub apertures, and finally estimates Doppler coefficient and target speed by the phase difference. The algorithm not only can obtain the speed of a moving target with high precision and further improve the imaging quality, but also greatly reduces the operation amount, can realize real-time estimation, has strong noise immunity and better estimation efficiency under sparse data, can be applied to long-distance, all-weather and macro-scale real-time detection of the moving target such as a vehicle, a ship and the like, improves the speed estimation precision of the moving target by interference processing of sub-aperture signals, and improves the imaging quality of the moving target, thereby being a reliable technical support for long-distance, all-weather and macro-scale real-time detection of the moving target such as the vehicle and the ship speed.
Drawings
FIG. 1 is a flow chart of a target speed estimation method based on sub-aperture radar interferometry according to the present invention;
FIG. 2 radar SAT-1 radar image contrast schematic of a stationary vessel and a mobile vessel;
FIG. 3 is a schematic diagram of actual SAR echo signal slope distance compression and signal phase unwrapping;
FIG. 4 is a schematic diagram of a simulated synthetic aperture radar signal phase trajectory;
FIG. 5 is a graph comparing Doppler coefficient estimates with noise at different sub-aperture data lengths;
FIG. 6 is a diagram showing the comparison of the result of the sub-aperture interferometry and the phase unwrapping combined with the least squares method with the Cramer-Rao bound.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments.
The following simulation actual scene example illustrates the target speed estimation method based on sub-aperture radar interference.
Actual scene example: FIG. 1 radar SAT-1 radar image contrast of a stationary vessel and a mobile vessel.
As shown in fig. 1, S1: changing the phases of echo signals according to the moving object, acquiring a plurality of phases of echo signals of the moving object, and the relative speed and the relative distance between the antenna and the moving object, acquiring the echo signals of the moving object, and determining the speed component relation with the object;
the relative distance relation between the antenna and the target object is
Wherein,is a relative distance vector; />For the relative velocity vector of the antenna and the object, +.>For the antenna speed vector, ">Is a target velocity vector;
the relation between the echo signal and the distance vector is that
Wherein A (t) represents the amplitude of the signal, lambda is the wavelength,is a distance vector;
within a sufficiently small time intervalTaylor series (Taylor series) expansion, greater than t 3 Is negligible and +.>Is far greater than the speed
Where a, b is the ratio factor a=v between the antenna speed and the target speed component x /U,b＝v y /U，v x ,v y The velocity components of the velocity of the moving object in the range (range) and azimuth (azimuth) directions are respectively represented,represents the antenna speed, typically |a|, |b| < 1, and is constant. The mathematical expression of the echo signal of the moving object can be written as the mathematical expression of the bird song pattern
Where y=ut denotes the position of the antenna in the synthetic aperture, the amplitude a (y) is real and does not affect the estimation result, f 0 ，f 1 ，f 2 The initial phasor, the initial frequency, and the rate of change of frequency, respectively.
As shown in fig. 2 (a) for a stationary ship image and fig. 2 (b) for a moving ship image, both images were from the sea surface radar sat-1 image at 3 months of 2000. The difference in the images of the stationary and moving objects is apparent from fig. 1, and the stationary ship image is clearly seen in fig. 2 (a), while the moving ship image is blurred and not easily recognized in fig. 2 (b). The invention solves the defects of unknown phase shift and distance movement generated by target movement and image quality reduction. FIG. 2 is a schematic diagram showing radar image contrast of a stationary ship and a moving ship of RADASAT-1.
S2: the echo signal is modularized into a polynomial signal mixed with Gaussian noise, the original aperture of the synthetic aperture radar is divided into a plurality of sub apertures with equal length, and then signals of a plurality of sub apertures are obtained through output;
the synthetic aperture radar echo signal pattern is a discrete signal of a quadratic polynomial and is typically contaminated by noise, given that it is additive noise:
s(y)＝e -jψ(y) +n(y)，y∈(0，Y)
wherein ψ (η) =f 0 +f 1y +f 2 y 2 Is the phase of the signal, which is in the form of a bird song; y total length of sample; n (y) is Gaussian and uncorrelatedComplex noise.
The data contained in the original aperture is divided into M sub-apertures, each sub-aperture has a data length N, the sub-aperture length is DeltaY=N r, and r is a sampling interval.
The interference phase of the j (j= 0,1,2,3L) th pen is the interference result of the j and j+1 sub-aperture data, and the relation is that
Similarly, the j+1th pen has an interference phase of
The j and j+1 phases are interfered with each other, so that the signal of the sub-aperture is interfered to generate a phase difference containing a second order coefficient
Wherein,the interference phases of the j+1th and j th strokes, respectively, ΔY being the sub-aperture length, +.>Is interference noise, f 2 Is the rate of change of frequency.
S3, generating a phase difference containing a second-order coefficient by interference processing of the signals of the plurality of sub-apertures;
FIG. 3 is a graph showing actual SAR echo signal slope distance compression and signal phase unwrapping; fig. 3 (a) shows the result of compressing an actual synthetic aperture radar echo signal by a slant distance, and fig. 3 (b) shows the result of phase unwrapping a certain signal in fig. 3 (a), which is expected to be in the form of a quadratic curve, i.e. in the form of a bird song signal.
S4: after demodulating the original signal, calculating a first-order Doppler coefficient obtained by estimating the Doppler coefficient and the target speed from the phase difference to obtain an estimated value of the initial frequency, wherein the estimated value is shown as a simulated synthetic aperture radar signal phase trajectory diagram in FIG. 4;
s5, calculating a slope distance direction speed component through the estimated value of the initial frequency so as to estimate the speed of the moving object with high precision.
The phase difference obtained frequency slope containing second-order coefficient is generated by the interference processing of the signal of the sub-aperture
Averaging to further suppress noise
The interference phase of the j-th penInterference is available
The initial frequency is f 1i .
The result after averaging is
Wherein, M original aperture data is divided into sub-componentsThe number of aperture data, N per sub-aperture data length,generating phase difference containing second order coefficient for signals of adjacent sub-apertures through interference treatment>Phase difference comprising first order coefficient, which is sub-aperture self-coherence,/->To interfere with noise, the longer the sub-aperture is, the more the estimated result is offset.
FIG. 5 is a graph showing comparison of Doppler coefficient estimation values with noise at different sub-aperture data lengths, respectively comparing true values f 2 ,f 1 Numerical results for sub-aperture data lengths n=1 and n=18. Wherein FIG. 5 (a) is the frequency slope of the sub-aperture signal after interference processingFIG. 5 (b) is the result of comparison of the estimated values of (a) and (b)>Is a result of the comparison of the estimated values of (a). Gaussian noise is added in fig. 5, and the deviation (displacement) of the noise is 0.0001. It is apparent from fig. 5 that the doppler coefficient estimation is discrete and significantly deviates from the true value f when the sub-aperture data length n=1 2 ,f 1 The estimated value of the Doppler coefficient is very close to the true value when the length of the sub-aperture data is N=18, and the estimated result is better. The results indicate that longer sub-apertures have better noise suppression capability. The deviation of the estimated result caused by too long sub-aperture is avoided, and the requirement of +.>
Under different signal-to-noise ratios, the estimation results of the sub-aperture interferometry and the phase unwrapping method combined with the least square method are compared with the Cramer-Rao bound (Cramer-Rao bound), so that the speed and the efficiency of the method in estimating the movement of the target are verified.
The definition given for the Cramer-Rao belts (CRLB) is
Testing under different signal-to-noise ratios, the estimated results of the subaperture interferometry and the phase unwrapping combined with the least squares method were compared with the craamer-Rao bound (Cramer-Rao bound), and the mean square error (mean square error, MSE) of the estimated values and the true values were defined as:
wherein f represents a true value (initial frequency f 1 Or the frequency slope f 2 )；An i-th estimated value with respect to f; m represents the total test times;
to further verify the efficiency of the present invention in estimating moving target velocity, fig. 6 tests the results of comparing the results of the estimation of sub-aperture interferometry and phase unwrapping with the least squares method with the Cramer-Rao bound (Cramer-Rao bound) at different signal-to-noise ratios (Signal noise ratio, SNR). Each group was tested 200 times at signal to noise ratio, the noise change varied from 37.0478 to-2.9878, the total sample number of data m=185. The x-axis in fig. 6 is the dB value of SNR, and the y-axis is the mean square error (mean square error, MSE) of the estimated value and the true value. As can be seen from comparison of the results of FIG. 6, the present invention can effectively estimate the velocity of a moving object by estimating the phase coefficient of the echo signal by using the sub-aperture dry-emission method, and has the following advantages: the operation amount is greatly reduced, and real-time estimation can be realized; (2) high noise immunity; (3) The amplitude change of the echo signal has no influence on the estimation result; (4) the method has better estimation efficiency under sparse data.
The foregoing is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art, who is within the scope of the present invention, should make equivalent substitutions or modifications according to the technical scheme of the present invention and the inventive concept thereof, and should be covered by the scope of the present invention.
Claims (2)
1. The target speed estimation method based on sub-aperture radar interference is characterized by comprising the following steps of:
s1: changing the phases of echo signals according to the moving object, acquiring a plurality of phases of echo signals of the moving object, and the relative speed and the relative distance between the antenna and the moving object, acquiring the echo signals of the moving object, and determining the speed component relation with the object;
s2: the echo signal is modularized into a polynomial signal mixed with Gaussian noise, the original aperture of the synthetic aperture radar is divided into a plurality of sub apertures with equal length, and then signals of a plurality of sub apertures are obtained through output;
s3, generating a phase difference containing a second-order coefficient by interference processing of the signals of the plurality of sub-apertures;
s4: after demodulating the original signal, estimating a Doppler coefficient and a target object speed by the phase difference to obtain a first-order Doppler coefficient, and calculating to obtain an estimated value of an initial frequency;
s5, calculating a slope distance direction speed component through the estimated value of the initial frequency so as to estimate the speed of the moving target object with high precision;
wherein the formula of the velocity component of the target in step S1 is
Amplitude a (y) is real and its variation does not affect the estimation result; y=ut represents the position of the antenna in the synthetic aperture;is the relative distance between the antenna and the target; a, b are the antenna speed and the target speedScale factor a=v between degree components x /U,b＝v y /U，v x ,v y Speed components of the speed of the moving object in the directions of the range and azimuth, respectively, +.>Represents the antenna speed, |a|, |b| < 1, and is a constant; f (f) 0 ，f 1 ，f 2 Respectively an initial phasor, an initial frequency and a rate of change of frequency;
the calculation formula of the polynomial signal mixed with Gaussian noise is as follows:
s(y)＝e -jψ(y) +n(y)，y∈(0，Y)
wherein ψ (y) =f 0 +f 1 y+f 2 y 2 Is the phase of the signal, which is in the form of a bird song; y total length of sample; n (y) is gaussian and uncorrelated complex noise;
dividing data contained in an original aperture into M sub-apertures, wherein each sub-aperture has a data length N, the sub-aperture length is delta Y=N r, and r is a sampling interval;
mutually interfering the j and j+1 phases to obtain a signal of the sub-aperture, and generating a phase difference containing a second-order coefficient by interference treatment, wherein the phase difference is as follows:
wherein,the interference phases of the j+1th and j th strokes, respectively, ΔY being the sub-aperture length, +.>Is interference noise, f 2 Is the rate of change of frequency.
2. The method for estimating a target speed based on sub-aperture radar interferometry according to claim 1, wherein the method for calculating the estimated value of the initial frequency comprises:
estimate of initial frequency:
wherein M is the number of the data of the original aperture data dividing the sub-aperture data, N is the length of each sub-aperture data,generating phase difference containing second order coefficient for signals of adjacent sub-apertures through interference treatment>Phase difference comprising first order coefficient for sub-aperture self-coherence,>to avoid the deviation of the estimation result caused by the longer sub-aperture for interference noise, the requirement of +.>
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102508244A (en) * | 2011-11-08 | 2012-06-20 | 中国人民解放军国防科学技术大学 | Ground moving target detection and parameter estimation method |
| EP2725382A1 (en) * | 2012-10-26 | 2014-04-30 | Astrium GmbH | Synthetic aperture radar for simultaneous imaging and moving target detection |
| CN109814100A (en) * | 2019-01-31 | 2019-05-28 | 西安电子科技大学 | SAR Ground moving target imaging method based on sub-aperture parameter Estimation |
| CN111208512A (en) * | 2020-01-15 | 2020-05-29 | 电子科技大学 | Interferometric measurement method based on video synthetic aperture radar |
-
2021
- 2021-04-22 CN CN202110437317.1A patent/CN113219451B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102508244A (en) * | 2011-11-08 | 2012-06-20 | 中国人民解放军国防科学技术大学 | Ground moving target detection and parameter estimation method |
| EP2725382A1 (en) * | 2012-10-26 | 2014-04-30 | Astrium GmbH | Synthetic aperture radar for simultaneous imaging and moving target detection |
| CN109814100A (en) * | 2019-01-31 | 2019-05-28 | 西安电子科技大学 | SAR Ground moving target imaging method based on sub-aperture parameter Estimation |
| CN111208512A (en) * | 2020-01-15 | 2020-05-29 | 电子科技大学 | Interferometric measurement method based on video synthetic aperture radar |
Non-Patent Citations (2)
| Title |
|---|
| 复杂背景下单通道SAR运动目标检测方法;高飞 等;《哈尔滨工程大学学报》;第32卷(第3期);第304-308页 * |
| 子带子孔径ATI地面运动目标检测及参数估计方法;周红 等;《电子与信息学报》;第32卷(第1期);第62-68页 * |
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