CN111123214B - Polynomial rotation-polynomial Fourier transform high-speed high-maneuvering target detection method - Google Patents
Polynomial rotation-polynomial Fourier transform high-speed high-maneuvering target detection method Download PDFInfo
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- G—PHYSICS
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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
- 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
- G01S7/28—Details of pulse systems
- G01S7/285—Receivers
- G01S7/32—Shaping echo pulse signals; Deriving non-pulse signals from echo pulse signals
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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
- G01S13/04—Systems determining presence of a target
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- 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
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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
- G01S7/28—Details of pulse systems
- G01S7/285—Receivers
- G01S7/295—Means for transforming co-ordinates or for evaluating data, e.g. using computers
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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
- G01S7/415—Identification of targets based on measurements of movement associated with the target
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Abstract
The invention discloses a polynomial rotation-polynomial Fourier transformation high-speed high-mobility target detection method, which comprises the steps of respectively performing digital sampling and pulse compression processing on M radar pulse echoes in accumulation time to obtain a fast-slow two-dimensional radar echo data matrix; then determining the order and range of the search parameter set according to the motion characteristics of the target to be detected and initializing the search parameter set; performing coherent accumulation on the data matrix in the whole parameter search space by utilizing polynomial rotation-polynomial Fourier transformation to obtain a distance-Doppler distribution diagram; finally, whether the target exists or not is judged by utilizing the constant false alarm detection, and if the target exists, the distance and the motion state information of the target can be obtained. The polynomial rotation-polynomial Fourier transform can achieve the same theoretical optimal accumulation effect with the polynomial rotation-polynomial Fourier transform under the condition that the computational complexity is far less than Yu Anyi radon transform, and realize the coherent accumulation of high-speed and high-maneuvering targets in the near space under the environment of low signal-to-noise ratio.
Description
Technical Field
The invention belongs to the technical field of radar signal processing and detection, and particularly relates to a polynomial rotation-polynomial Fourier transform high-speed high-maneuvering target detection method.
Background
In recent years, with the development of scientific technology, the appearance of high-speed and high-maneuvering targets in the near space brings serious challenges to radar detection, such as fighters and missiles with ultrahigh sound speed and high maneuvering in the air defense field, track targets and space fragments needing to be monitored in space, and the like. Some target flying speeds can reach 25 Mach, and the flying track can be changed in various irregular modes such as overturning, jumping, large corners and the like, so that the device has extremely strong maneuverability. In addition, due to the maturity of stealth technology and plasma generated by high-speed movement of the aircraft in the atmosphere, the signal-to-noise ratio of target echo is lower, and the detection performance of the radar is reduced.
Pulse coherent accumulation is an effective method for improving target detection probability, and prolonging radar fixation target time is an effective means for improving low signal-to-noise ratio target coherent accumulation gain. However, the target ultra-high speed and high mobility impose certain limitations on the accumulation time. On the one hand, the high speed of the target causes the target to appear a spanning gate phenomenon in the distance dimension within the accumulation time; on the other hand, the high mobility of the target causes a doppler frequency migration phenomenon in the doppler frequency dimension of the target.
The current coherent accumulation mainly surrounds a Moving Target Detection (MTD) technology, keystone transformation and Radon Fourier transformation and expansion and development of the technology. Most of the existing methods utilize a time-frequency analysis method to estimate the target motion parameters after correcting the distance walking. However, when the nonlinear distance walk and Doppler walk of the target are caused by higher-order motion parameters such as acceleration of the target, most of the existing methods are difficult to realize the distance walk correction and the Doppler walk compensation at the same time, so that the theoretical detection performance cannot be achieved.
Disclosure of Invention
The invention aims to provide a polynomial rotation-polynomial Fourier transform high-speed high-maneuvering target detection method which is suitable for detecting a near space high-speed high-maneuvering target.
The technical solution for realizing the purpose of the invention is as follows: a polynomial rotation-polynomial fourier transform high-speed high maneuver target detection method comprising:
step 1, performing digital sampling and pulse compression processing on radar pulse echoes in accumulation time to obtain a two-dimensional echo data matrix;
step 2, determining the number and the range of parameters to be searched;
step 3, performing polynomial rotation transformation on the two-dimensional echo data matrix from the initial search parameter set, and performing non-coherent accumulation on the transformed echo data matrix; if the maximum value of the superimposed one-dimensional data is greater than the threshold value, performing polynomial Fourier transform in the step 4 on the transformed echo data matrix; otherwise, changing the search parameter set to execute the step 3;
step 4, performing phase compensation on the search parameter sets meeting the conditions in the step 3, accumulating, and then modifying the search parameter sets to execute the step 3 until the complete search parameter sets are traversed;
step 5, performing constant false alarm detection on the obtained distance-Doppler distribution diagram, and judging whether a target exists or not;
and 6, determining coordinates of the position of the target, and determining the motion parameters of the target.
Compared with the prior art, the invention has the remarkable advantages that: the polynomial rotation-polynomial Fourier transform can achieve the same theoretical optimal accumulation effect with the polynomial rotation-polynomial Fourier transform under the condition that the computational complexity is far less than Yu Anyi radon transform, and realize the coherent accumulation of high-speed and high-maneuvering targets in the near space under the environment of low signal-to-noise ratio.
Drawings
FIG. 1 is a flow chart of a method for high-speed and high-mobility object detection of the polynomial rotation-polynomial Fourier transform of the present invention.
Figure 2 is an MTD accumulated range-doppler profile.
Figure 3 is a PRPFT accumulated range-doppler profile.
FIG. 4 is a graph of the results of single PRT non-coherent accumulation.
Detailed Description
As shown in fig. 1, in the polynomial rotation-polynomial fourier transform (PRPFT) high-speed high-mobility target detection method of the present invention, firstly, M radar pulse echoes in accumulation time are respectively subjected to digital sampling and pulse compression processing, so as to obtain a fast-slow-time two-dimensional radar echo data matrix; then determining the order and range of the search parameter set according to the motion characteristics of the target to be detected and initializing the search parameter set; performing coherent accumulation on the data matrix in the whole parameter search space by utilizing polynomial rotation-polynomial Fourier transformation to obtain a distance-Doppler distribution diagram; finally, whether the target exists or not is judged by utilizing the constant false alarm detection, and if the target exists, the distance and the motion state information of the target can be obtained. The method comprises the following specific steps:
step 1: echo signal sampling and pulse compression
Sampling and pulse compressing the echo signals of M periods of coherent accumulation to obtain a two-dimensional echo data matrix s (N, M), wherein N represents the distance dimension sampling point marks, n=1, 2, & gt, N, N is the total number of single period echo sampling points, M represents the echo signal number marks, m=1, 2, & gt, and M, M is the total number of coherent accumulation echoes;
step 2: determining parameter search ranges
Determining the number and the range of parameters to be searched according to the actual conditions of the radar and the target to be detected;
setting the search speed range as [ v ] min ,v max ]Wherein is v min Is the lower bound of the speed search range, v max Is the upper bound of the speed search range; setting the speed search interval thereof to be Δv, Δv=λ/2T, wherein λ is the carrier wavelength, and T is the accumulation time; with N v Speed search points, N v ＝round((v max -v min ) V), wherein round (·) is a rounding function; setting the search acceleration range as [ a ] min ,a max ]Wherein is a min Is the lower bound of the acceleration search range, a max Is the upper bound of the acceleration search range; setting the acceleration search interval as delta a, N a Search points of acceleration, N a ＝round((a max -a min ) /Δa); if higher-order motion parameters exist, the parameter searching ranges are set in sequence. Determining a set of search parameters (alpha) 1 ,α 2 ,...,α k ) Wherein alpha is i I=1, 2,..k corresponds to the target i-th order motion parameter and α i Comprising N i The number of search points.
Step 3: polynomial rotation transformation
From an initial set of search parameters (alpha) 1 ,α 2 ,...,α k ) The polynomial rotation transformation is started on the two-dimensional echo data matrix s (n, m) to obtain a rotated data matrix s (n ', m'), and the transformation relation is as follows:
wherein B is the bandwidth of the linear frequency modulation signal, T r For pulse repetition interval, c is the speed of light. And carrying out non-coherent accumulation on the transformed echo data matrix, namely superposing M echo signal envelopes. If the maximum value of the superimposed one-dimensional data is greater than the threshold A th Then the polynomial Fourier transform in step 4 is performed on s (n ', m'), threshold A th Is that
Wherein abs (·) is a modulus function, N is the total number of single-period echo sampling points, and M is the total number of coherent accumulated echoes; otherwise, the step 3 is executed by changing the search parameter set.
Step 4: polynomial fourier transform
The search parameter group meeting the condition in the step 3 is subjected to phase compensation and then accumulated, and the method is as follows
Where s (n ', m') is the rotated transformed data matrix, (α) 1 ,α 2 ,...,α k ) To search the parameter set, lambda is the carrier wavelength, T r For the pulse repetition interval. And then changing the search parameter set to execute the step 3 until the complete search parameter set is traversed.
Step 5: constant false alarm detection
And (3) performing constant false alarm detection on the obtained distance-Doppler distribution diagram, and judging whether the target exists or not.
Step 6: motion parameter estimation
And determining coordinates of the position of the target, and determining the motion parameters of the target.
The present invention will be described in detail with reference to the following examples and drawings.
Examples
A polynomial rotation-polynomial fourier transform high-speed high maneuver target detection method comprising:
step 1: the M periodic radar signal echoes within the radar coherent accumulation time T are respectively sampled at the frequency f s And performing digital sampling, and then performing pulse compression processing on the sampled data to obtain a fast-slow two-dimensional radar echo data matrix s (n, m). Where N represents the distance dimension sampling point index, n=1, 2, & gt, N is the total number of single period echo sampling points, M represents the echo signal number index, m=1, 2, & gt, M is the total number of coherent accumulated echoes.
Step 2: aiming at the motion state of higher order above the acceleration of the high-speed and high-maneuvering target to be detected, setting the search speed range as [ v ] min ,v max ]Wherein is v min Is the lower bound of the speed search range, v max Is the upper bound of the speed search range. The speed search interval is set to Δv, Δv=λ/2T, where λ is the carrier wavelength and T is the accumulation time. With N v Speed search points, N v ＝round((v max -v min ) V), wherein round (·) is a rounding function; setting the search acceleration range as [ a ] min ,a max ]Wherein is a min Is the lower bound of the acceleration search range, a max Is the upper bound of the acceleration search range. Setting the acceleration search interval to be deltaa, deltaa=lambda/4T 2 . With N a Search points of acceleration, N a ＝round((a max -a min ) /Δa); if higher-order motion parameters exist, the parameter searching ranges are set in sequence. Determining a set of search parameters (alpha) 1 ,α 2 ,...,α k ) Wherein alpha is i I=1, 2,..k corresponds to the target i-th order motion parameter and α i Comprising N i Individual searchesPoints.
For convenience of explanation, ignoring the third order and above motion parameters of the radar target in the following detailed description, that is, the target makes uniform acceleration linear motion relative to the radar, the search parameter set may be determined to be (v, a), and the initialization parameter set may be determined to be (v min ,a min )。
Step 3: the polynomial rotation transformation relation can be obtained by utilizing the search parameter set
Wherein (v) i ,a j ) For the current search parameter set, B is the bandwidth of the linear frequency modulation signal, T r For pulse repetition interval, c is the speed of light. Transforming s (n, m) into s (n ', m') by using a polynomial rotation transformation relation to obtain a rotated fast-slow two-dimensional echo data matrix, and performing non-coherent accumulation on radar echo in a slow time dimension, wherein the method is as follows
Where abs (·) is the modulo function. Setting threshold A th Is that
When max (R (n')) > A th And (3) if yes, performing polynomial Fourier transform in the step (3), otherwise, updating the search parameter set, and performing polynomial rotation transform again until the complete search parameter set is traversed.
Step 4: for the current search parameter set (v i ,a j ) And performing polynomial Fourier transform to realize coherent accumulation. The polynomial rotation transformation screens out possible search parameter groups to carry out polynomial Fourier transformation, so that the algorithm calculation complexity is reduced. The Fourier transform is as follows
Wherein s (n ', m') is a data matrix after rotation transformation, (v) i ,a j ) To search the parameter set, lambda is the carrier wavelength, T r For the pulse repetition interval. Then updating the search parameter set to execute step 3 until the complete search parameter set is traversed.
The method (v, a) for traversing the entire search parameter set is as follows: the total number of cycles is N v N a Let the current number of cycles be k, k=1, 2 v N a Let the k-th set of search parameters be (v) i ,a j ) Where i=floor (k/N v ) Floor (·) is a downward rounding function, j=mod (k, N) v ) Mod (·) is a remainder function. k=n v N a Representing that the entire search parameter space is traversed over. At this time, a range-doppler profile after coherent accumulation can be obtained.
Step 5: constant false alarm detection is carried out on the distance-Doppler distribution diagram, whether an object exists or not is judged, and the judgment method is as follows
Where (vi, aj) is the search parameter set, η is the detection threshold, and N is the total number of single-period echo sampling points. If the amplitude value of the detection unit is high Yu Menxian, the detection unit is judged to have the target, otherwise, the detection unit is judged to have no target, and the detection processing of the subsequent unit is continued.
Step 6: if the target exists, extracting the target position information as n' and the speed information as v i Acceleration information a j 。
The effect of the invention is verified by Matlab as follows:
the simulation parameters are set as follows: carrier frequency f 0 =1 GHz, pulse width t=60 us, bandwidth b=2 MHz, pulse repetition frequency T r =600us, accumulated pulse number N pulse =64, sampling frequency f s =4mhz, initial distance of target R 0 =4000 km, radial initial velocity V 0 4000m/s, acceleration a=100 m/s 2 。
Simulation results and analysis: as can be seen from fig. 2, the conventional MTD algorithm suffers from poor accumulation performance in the face of high-speed high maneuver targets. The target distance walk causes a large deviation of a target estimated distance unit, and the Doppler migration causes that target energy cannot be well gathered through FFT. Thus the final accumulation performance cannot reach the requirement of constant false alarm detection. As can be seen from fig. 3, the energy after target accumulation after polynomial rotation-polynomial fourier transformation is well aggregated, which is significantly better than the MTD algorithm. Fig. 4 shows the result of PRT non-coherent accumulation, and it can be seen that the peak of the target energy is obvious but the noise floor is too high, which is not suitable for target detection, but only for the reference of whether the target exists.
Claims (6)
1. A polynomial rotation-polynomial fourier transform high-speed high maneuver target detection method comprising:
step 1, performing digital sampling and pulse compression processing on radar pulse echoes in accumulation time to obtain a two-dimensional echo data matrix;
step 2, determining the number and the range of parameters to be searched;
step 3, performing polynomial rotation transformation on the two-dimensional echo data matrix from the initial search parameter set, and performing non-coherent accumulation on the transformed echo data matrix; if the maximum value of the superimposed one-dimensional data is greater than the threshold value, performing polynomial Fourier transform in the step 4 on the transformed echo data matrix; otherwise, changing the search parameter set to execute the step 3; the specific method comprises the following steps:
from an initial set of search parameters (alpha) 1 ,α 2 ,...,α k ) Starting polynomial rotation transformation of the two-dimensional echo data matrix s (n, m) to obtain a rotated data matrix s (n ', m'), wherein α i Corresponding to the ith order motion parameter of the target and alpha i Comprising N i The number of search points, N represents distance dimension sampling point marks, n=1, 2, & gt, N are the total number of single period echo sampling points, M represents echo signal number marks, m=1, 2, & gt, M are coherent accumulated echoesA total number;
the transformation relationship is as follows:
where k is polynomial order, B is chirp bandwidth, T r The pulse repetition interval is the pulse repetition interval, and c is the light speed; non-coherent accumulation is carried out on the transformed echo data matrix, namely M echo signal envelopes are overlapped; if the maximum value of the superimposed one-dimensional data is greater than the threshold A th Then the polynomial Fourier transform in step 4 is performed on s (n ', m'), threshold A th Is that
Wherein abs (·) is a modulo function;
otherwise, changing the search parameter set to execute the step 3;
step 4, performing phase compensation on the search parameter sets meeting the conditions in the step 3, accumulating, and then modifying the search parameter sets to execute the step 3 until the complete search parameter sets are traversed;
step 5, performing constant false alarm detection on the obtained distance-Doppler distribution diagram, and judging whether a target exists or not;
and 6, determining coordinates of the position of the target, and determining the motion parameters of the target.
2. The method for detecting a high-speed and high-mobility target by polynomial rotation-polynomial fourier transform according to claim 1, wherein step 1 specifically comprises:
and sampling the echo signals of M periods which are coherently accumulated and performing pulse compression processing to obtain a two-dimensional echo data matrix s (n, M).
3. The polynomial rotation-polynomial fourier transform high-speed high maneuver target detection method as recited in claim 1, whereinIn step 2, specifically: setting the search speed range as [ v ] min ,v max ]Wherein v is min Is the lower bound of the speed search range, v max Is the upper bound of the speed search range; setting the speed search interval thereof to be Δv, Δv=λ/2T, wherein λ is the carrier wavelength, and T is the accumulation time; with N v Speed search points, N v ＝round((v max -v min ) V), wherein round (·) is a rounding function; setting the search acceleration range as [ a ] min ,a max ]Wherein a is min Is the lower bound of the acceleration search range, a max Is the upper bound of the acceleration search range; setting the acceleration search interval as delta a, N a Search points of acceleration, N a ＝round((a max -a min ) /Δa); if higher-order motion parameters exist, the parameter searching range is set in sequence; determining a set of search parameters (alpha) 1 ,α 2 ,...,α k )。
4. The method for detecting a high-speed and high-mobility target by polynomial rotation-polynomial fourier transform according to claim 1, wherein step 4 specifically comprises:
the search parameter group meeting the condition in the step 3 is subjected to phase compensation and then accumulated, and the method is as follows
Where s (n ', m') is the rotated transformed data matrix, (α) 1 ,α 2 ,...,α k ) To search the parameter set, lambda is the carrier wavelength, T r For a pulse repetition interval; and then changing the search parameter set to execute the step 3 until the complete search parameter set is traversed.
5. The method for detecting a high-speed and high-mobility target by polynomial rotation-polynomial fourier transform according to claim 1, wherein step 5 specifically comprises:
and (3) performing constant false alarm detection on the distance-Doppler distribution diagram, and judging whether a target exists or not, wherein the judging method comprises the following steps:
in the formula (v) i ,a j ) For searching parameter groups, eta is a detection threshold, and N is the total number of single-period echo sampling points; if the amplitude value of the detection unit is high Yu Menxian, the detection unit is judged to have the target, otherwise, the detection unit is judged to have no target, and the detection processing of the subsequent unit is continued.
6. The method for high-speed, high-mobility object detection by polynomial rotation-polynomial fourier transform of claim 1, wherein the object motion parameters in step 6 include object velocity and acceleration information.
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| CN112255609A (en) * | 2020-10-14 | 2021-01-22 | 哈尔滨工业大学 | Constant-acceleration maneuvering target coherent accumulation detection method |
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