CN111650571B - Micro-motion period-based single-channel blind source separation method for space micro-motion group target - Google Patents
Micro-motion period-based single-channel blind source separation method for space micro-motion group target Download PDFInfo
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- CN111650571B CN111650571B CN202010282521.6A CN202010282521A CN111650571B CN 111650571 B CN111650571 B CN 111650571B CN 202010282521 A CN202010282521 A CN 202010282521A CN 111650571 B CN111650571 B CN 111650571B
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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
Abstract
The invention discloses a micro-motion period-based single-channel blind source separation method for a space micro-motion group target, which comprises the following steps: firstly, transmitting a single-frequency pulse signal to obtain single-channel mixed complex micro-motion echoes of a plurality of warheads, then segmenting and rearranging the mixed echoes into a matrix form, calculating a singular value ratio by using a singular value decomposition method, extracting a maximum peak value and estimating the micro-motion period of each target; and segmenting and superposing the mixed echoes according to periods, averaging, and obtaining the micro-motion echo data of each target in one period by a cyclic iteration method. The invention utilizes the prior knowledge that the micro-motion periods of all warheads are different, directly filters the mixed signal in the time domain and improves the precision of signal separation.
Description
Technical Field
The invention belongs to the technical field of signal processing, and particularly relates to a spatial micro-motion group target single-channel blind source separation method based on a micro-motion period.
Background
The flight trajectory of a strategic trajectory missile can be divided into: a boost section, a mid-section, and a reentry section. The boosting section is located in the detectable range of the enemy, the flight time of the reentry section is short, the flight duration of the middle section warhead is long and stable, and the boosting section is used as the optimal stage for detecting the enemy missile. When the missile flies in the middle section, because no atmospheric resistance exists, most baits and fragments formed by explosion of the female bin do rolling motion under the condition of no attitude controller, and only the true warhead with the attitude control and the individual bait warhead do precession or nutation and fly according to a set track. Furthermore, the infrared detection means is substantially ineffective, since in the middle section the infrared radiation capability is substantially lost. The early warning radar has the characteristics of long acting distance, all-time and all-weather, and plays an important role in the aspects of detection, identification, interception, killing evaluation and the like of strategic trajectory missiles.
The group target formed in the middle section area seriously interferes with the operation of a missile defense system, and when the radar detects the mixed echoes of a plurality of targets, the targets are mutually overlapped and inseparable in the time domain and the frequency domain. The traditional single-channel blind source separation problem is that an observation signal is decomposed into a series of detail signals and approximate signals through some decomposition methods, such as wavelet decomposition, empirical mode decomposition and the like, the detail signals and the approximate signals form a virtual multi-channel form with the observation signal, and then separation is carried out by utilizing a classical Independent Component Analysis (ICA) method. However, the decomposition method and the selected component signals are improper, which can affect the separation of the signals. Another common method is to convert the signal into a sparse domain, such as a time-frequency domain, separate the signal by using the sparsity of the signal in the transform domain, and then transform the signal back to the time domain. However, warhead micro-motion signals are mutually overlapped in a time-frequency domain, and a sparse transform domain cannot be found.
Disclosure of Invention
The invention aims to provide a spatial micro-motion group target single-channel blind source separation method based on a micro-motion period.
The technical solution for realizing the purpose of the invention is as follows: a micro-motion period-based spatial micro-motion group target single-channel blind source separation method comprises the following steps:
and 3, performing segmented superposition on the micro-motion mixed echoes respectively according to the estimated period, performing averaging operation to obtain a roughly estimated echo of each target in one period, subtracting the roughly estimated echoes of a plurality of targets from the mixed echoes respectively, only remaining the echo of one target, performing segmented superposition averaging on the obtained echoes again according to the period of the target, and performing cyclic iteration all the time to finally obtain an accurate complex echo of each target in one period.
Compared with the prior art, the invention has the remarkable advantages that: (1) according to the method, different jogging periodic characteristics of a space jogging warhead are fully utilized, a 20s mixed signal is cut and rearranged into a matrix form according to different lengths, singular value decomposition is carried out, the ratio of a first singular value to a second singular value is calculated, the cut length is continuously changed, the period of a first target is extracted, a rough estimation echo of the target is estimated by a segmented superposition method, further residual echoes are obtained, the cutting is performed again, the rearrangement into the matrix is carried out, the period is estimated, and the process is repeated until the estimated period is finished; the method can effectively estimate the micro-motion period of each target; (2) and carrying out segmented superposition on the mixed echo according to the estimated period to obtain a coarse estimated echo of each target, wherein the longer the observation time is, the more the number of the superposed segments is, and the more accurate the estimated echo is. In order to solve the problem of long observation time, a cyclic iteration method can be adopted to gradually converge the target echo and improve the target signal separation precision.
Drawings
FIG. 1 is a flow chart diagram of a spatial micro-motion group target single-channel blind source separation method based on a micro-motion period.
FIG. 2 is a schematic diagram of a single radar cluster target system in accordance with the present invention.
Figure 3 is a graphical representation of the echo of each target of the ballistic missile of the present invention.
Figure 4 is a schematic diagram of the hybrid echo of a ballistic projectile group target in the present invention.
Figure 5 is a schematic diagram of a group target period obtained from a simulation of a ballistic projectile group target in accordance with the present invention.
Fig. 6 is a schematic diagram of a target segment stacking method for ballistic projectile groups in the invention.
FIG. 7 is a schematic representation of the position and size of three missiles in accordance with the present invention.
Figure 8 is a schematic diagram of the target echoes of ballistic projectile group targets separated according to the estimated micro-motion period of figure 5 in accordance with the present invention.
Detailed Description
The present invention is described in further detail below with reference to the attached drawing figures.
With reference to fig. 1, the method for separating a single-channel blind source of a spatial micro-motion group target based on a micro-motion period of the present invention comprises the following steps:
the duration of the single frequency pulse is 10-20 s, and the echo of each target can be obtained by transmitting the single frequency pulse with the duration of 20s as shown in FIG. 3. And receiving a single-channel complex mixed echo of the micro-group target in the time period, wherein the first target period is shown in figure 5 as shown in figure 4.
Step 1.1, the narrow-band pulse signals transmitted by the radar are as follows:
wherein, T r Is the signal pulse repetition period, f is the carrier frequency of the signal, τ is the pulse width of the signal, and:
the micro-motion echo of the warhead can be converted into the static state of the warhead, the relation between the radar line-of-sight angle and time is found through the corresponding change of the radar line-of-sight angle, and the echo when the warhead is in micro motion can be obtained according to the static warhead echo.
Assuming that the radar emits a 20s sheet, without considering the translational state of the warheadObtaining n warhead micro-motion echoes as s by the frequency pulse signal i (t), i ═ 1.., n. Then a hybrid echo can be obtained as:
X(t)＝s 1 (t)+s 2 (t)+…+s n (t) (3)
step 1.2, setting the number of cycles N N Converting the micro-motion mixed echo X of a single channel into a virtual multi-channel matrix form X j ：
Wherein, N j Denotes the number of sampling points per line in the j-th cycle, and X j Can be formed by M j ＝floor(N/N j ) It is decided that N represents the number of samples in the entire sequence, the function floor (·) represents rounding down, and they must satisfy the following equation to ensure that there are enough samples.
N≥M j ×N j (5)
Step 1.3, matrix X is aligned j Carrying out SVD decomposition:
U j Σ j (V j ) T ＝SVD(X j ) (6)
wherein U is [ U ] 1 ,…,u M ]∈R M×M ，V＝[v 1 ,…,v N ]∈R N×N And U T U＝I，V T V＝I，Σ∈R M×N As follows:
wherein σ 1 ≥…≥σ L ≥0
Extracting the first singular value sigma 1 And a second singular value σ 2 And calculates and saves the singular value ratio SVR ═ (σ) 1 /σ 2 ) The value of (c).
Step 1.4, setting a threshold value, extracting all peak values of singular value ratios which are greater than the threshold value condition, and when N is greater than the threshold value condition j Is a period ofThen, peaks exist at the multiple positions, the peaks with the multiple relation are extracted, and the time corresponding to the maximum peak is selected as the period of the first source signal;
step 2.1, suppose the estimated first target period is T 1 And the number of sampling points in the first period is N, the number of the sections obtained by segmenting the mixed echo according to the first period is as follows:
M＝floor(20/T 1 ) (8)
wherein floor (. cndot.) represents rounding down.
Correspondingly adding the obtained M sections of data, and averaging to obtain a rough estimation echo of the first target in one period:
step 2.2, repeating the rough estimation signal S ' of the first target for M times, splicing into a one-dimensional signal S ', subtracting S ' by using a mixed signal with the same length to obtain a residual signal:
x＝X-S′ (10)
estimating the period of the residual signal by using the method in the step 1 to obtain the period T of the second target 2 Obtaining a residual signal according to the method in the step 2, and estimating the period again until the estimated period is repeated with the estimated period;
step 3.1, assume that the estimated target number is nn and the period is T i I is 1, …, nn. Setting the loop n1 to be 1: loop, wherein the loop time is generally more than 500;
step 3.2, setting the calculation source signal cycle n2 to be 1: nn, and observing the signal according to T n2 Segment superposition is carried out and divided by the number of segments, thereby obtaining a first coarse estimation result s of each signal n2 ′；
Step 3.3, setting the loop n3 ≠ 1: nn, and when n3 ≠ n2, calculating the residual signal y ═ X-s n3 ' at this time, the signal y contains a large number of signal components of the n2 th signal component, and y is T-th signal component n2 And performing segmented superposition and dividing by the number of segments so as to correct the source signal and obtain a more accurate result. The loop is performed according to steps 3.1 to 3.3 until the number of loops is reached, the result of which is an estimate of the source signal component.
If the mean values of the other source signals are all zero, each signal is mutually staggered and accumulated, when the number of superposition times is large enough, the other source signals are added and averaged for multiple times and finally become zero, the signals with the period of T can be accurately separated, but in practical situations, each signal cannot be zero mean value, so that the finally separated signals are almost different from the data of the original signals in one period by a constant value, namely almost in a translation relation, and the separation similarity is high.
The difference between the real signal and the split signal can be determined, assuming that the split signal differs from the real signal by only a constant value for each value in a period, i.e.:
wherein S is i (N) represents the Nth sampling point of the ith real target,
the nth sampling point of the corresponding reconstruction signal is represented, and the number of sampling points in one period is N.
Add the two sides of the equation and average:
the difference between the real signal and the reconstructed signal is about delta i 。
In order to verify the correctness and effectiveness of the method of the present invention, an example of the spatial micro-motion group target blind source separation is given below.
The transmitting frequency is 1GHz, the observation time is 20s, the centroid position of the target 1 is (0, 0, 0), the height is 2.0m, the radius of the bottom surface is 0.35m, the precession is carried out around the Z axis of the coordinate system, the precession period is 1.1s, and the precession angle is 8 degrees; the position of the centroid of the target 2 is (3, 4, 0), the height is 2.0m, the radius of the bottom surface is 0.35m, the target swings around the centroid of the target, the swing period is 2.3s, and the swing angle is 5 degrees; the center of mass of the target 3 is (-3, 4, 0), the height is 1.5m, the radius of the bottom surface is 0.30m, the micro-motion form is nutation, the micro-motion form is precession around the Z axis of a coordinate system, the precession angle is 8 degrees, the micro-motion form swings around the center of mass of the micro-motion form, the swing angle is 3 degrees, and the nutation period is 1.9 s. The target size is schematically shown in fig. 7. The period obtained by the simulation is shown in fig. 5, the abscissa is the period, and the ordinate is the singular value ratio. Using the period obtained in FIG. 5, the method shown in FIG. 6 is used to obtain the three target echoes from the separated micro-motion echoes, as shown in FIG. 8. The results estimated by this method are shown in Table 1.
TABLE 1
| Degree of similarity | Relative root mean | |
| Target | ||
| 1 electric field | 99.99％ | 1.41 |
| Target | ||
| 2 electric field | 99.99％ | 0.24 |
| Target | ||
| 3 electric field | 99.99％ | 1.49％ |
As can be seen from Table 1, the separation errors of the three targets are all below 2%, the separation errors are very close to the source signals, the similarity is all above 99.9%, and the waveform goodness of fit is extremely high.
In summary, the present invention fully utilizes different micro-motion periods of the ballistic missile target, and for a source signal component with a period T, corresponding source signal echoes are the same in one period T, and a signal component with a period not being T is segmented according to T, and each time sub-segment echo is different.
Claims (5)
1. A micro-motion period-based single-channel blind source separation method for a space micro-motion group target is characterized by comprising the following steps:
step 1, transmitting single frequency pulse to a space warhead target, and receiving single-channel complex mixed echo of a micro-motion group target within pulse transmission duration; cutting and arranging the observation signal X into a matrix form with M rows and N columns, obtaining a plurality of matrixes by changing the column number of the matrixes, carrying out singular value decomposition on each matrix, and calculating the ratio of a first singular value to a second singular value; setting a threshold value, and extracting a maximum peak value meeting the condition, namely a first target period;
step 2, carrying out segmented superposition on warhead micro-motion mixed echoes according to an estimated first period, taking an average value to obtain a rough estimated echo of a first target, subtracting a rough estimated signal of the first target from the mixed echoes to obtain a residual signal, and repeating the estimated period to obtain periods of all targets;
and 3, performing segmented superposition on the micro-motion mixed echoes respectively according to the estimated period, performing averaging operation to obtain a roughly estimated echo of each target in one period, subtracting the roughly estimated echoes of a plurality of targets from the mixed echoes respectively, only remaining the echo of one target, performing segmented superposition averaging on the obtained echoes again according to the period of the target, and performing cyclic iteration all the time to finally obtain an accurate complex echo of each target in one period.
2. The micro-motion period-based spatial micro-motion swarm target single-channel blind source separation method according to claim 1, wherein the duration of a single frequency pulse in step 1 is 10-20 s.
3. The micro-motion period-based spatial micro-motion group target single-channel blind source separation method according to claim 1, wherein the specific method in step 1 is as follows:
step 1.1, the narrow-band pulse signals transmitted by the radar are as follows:
wherein, T r Is the signal pulse repetition period, f is the carrier frequency of the signal, τ is the pulse width of the signalDegree, and:
the micro-motion echo of the warhead can be converted into the static state of the warhead, the relation between the radar line-of-sight angle and time is found through the corresponding change of the radar line-of-sight angle, and the echo when the warhead is in micro motion is obtained according to the static state of the warhead echo;
when the translation state of the warhead is not considered, the radar is assumed to transmit a single-frequency pulse signal of 20s to obtain n warhead micro-motion echoes of s i (t), i ═ 1,. ·, n; then a hybrid echo can be obtained as:
X(t)＝s 1 (t)+s 2 (t)+…+s n (t) (3)
step 1.2, setting the number of cycles N N Converting the micro-motion mixed echo X of a single channel into a virtual multi-channel matrix form X j ：
Wherein N is j Represents the number of sample points per line in the j-th cycle, and X j Can be formed by M j ＝floor(N/N j ) It was decided that N represents the number of samples in the entire sequence, the function floor (. cndot.) represents rounding down, and N, N j And M j The following formula must be satisfied to ensure that there are enough sampling points;
N≥M j ×N j (5)
step 1.3, matrix X is aligned j Carrying out SVD decomposition:
U j ∑ j (V j ) T ＝SVD(X j ) (6) wherein U is [ U ] 1 ,…,u M ]∈R M×M ，V＝[v 1 ,…,v N ]∈R N×N And U T U＝I，V T V＝I，∑∈R M×N As follows:
wherein σ 1 ≥…≥σ L ≥0；
Extracting the first singular value σ 1 And a second singular value σ 2 And calculates and saves the singular value ratio SVR ═ (σ) 1 /σ 2 ) A value of (d);
step 1.4, setting a threshold value, extracting all peak values of singular value ratios which are greater than the threshold value condition, and when N is greater than the threshold value condition j When the source signal is a period, peaks exist at the multiple positions, the peaks with the multiple relation are extracted, and the time corresponding to the maximum peak is selected as the period of the first source signal.
4. The method for separating the single-channel blind sources of the targets of the spatial micro-motion group based on the micro-motion period according to claim 1, wherein the step 2 is to superpose the warhead micro-motion mixed echoes in a segmented manner according to the estimated first period, obtain an average value to obtain a coarse estimated echo of the first target, subtract the coarse estimated signal of the first target from the mixed echo to obtain a residual signal until the estimated period is repeated, and obtain the periods of all the targets, specifically as follows:
step 2.1, assume the estimated first target period to be T 1 And the number of sampling points in the first period is N, the number of the sections obtained by segmenting the mixed echo according to the first period is as follows:
M＝floor(20/T 1 ) (8)
wherein floor (·) denotes rounding down;
correspondingly adding the obtained M sections of data, and averaging to obtain a rough estimation echo of the first target in one period:
step 2.2, repeating the rough estimation signal S ' of the first target M times, splicing into a one-dimensional signal S ', subtracting S ' from the mixed signal with the same length to obtain a residual signal:
x＝X-S′ (10)
estimating the period of the residual signal by using the method in the step 1 to obtain the period T of the second target 2 And obtaining the residual signal according to the method in the step 2, and estimating the period again until the estimated period is repeated with the estimated period.
5. The method according to claim 1, wherein the step 3 is to separately segment and superimpose the mixed signals according to the estimated period, and perform an averaging operation to obtain the roughly estimated echoes of each target within one period, subtract the roughly estimated echoes of multiple targets from the mixed echoes respectively to leave only the echoes related to one target, segment and superimpose the obtained echoes again according to the period of the target, and perform a cyclic iteration until an accurate complex echo of each target within one period is obtained, which is specifically as follows:
step 3.1, assume that the estimated target number is nn and the period is T i I is 1, …, nn; setting loop n1 to 1: loop;
step 3.2, setting the calculation source signal cycle n2 to be 1: nn, and observing the signal according to T n2 Segment superposition is carried out and divided by the number of segments, thereby obtaining a first coarse estimation result s of each signal n2 ′；
Step 3.3, setting the loop n3 ≠ 1: nn, and when n3 ≠ n2, calculating the residual signal y ═ X-s n3 ', for y according to T n2 Performing segment superposition and dividing by the number of segments so as to correct the source signal; looping is performed according to the steps 3.1 to 3.3 until the number of loops is reached, and the result is the estimation of the source signal component;
and calculating the difference between the real signal and the separation signal, and assuming that each value of the separation signal and each value of the real signal in a period only differ by a constant value, namely:
wherein S is i (N) represents the Nth sampling point of the ith real target,
the Nth sampling point of the corresponding reconstruction signal is represented, and the number of sampling points in one period is N;
add the two sides of the equation and average:
the difference between the real signal and the reconstructed signal is about delta i 。
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