CN102176027B - High-dynamic-interference auto-tracking steady suppression method - Google Patents

Abstract

The invention discloses a high-dynamic interference auto-tracking steady suppression method which is mainly used for solving the problem that a normal anti-interference method is poor in dynamic interference suppression effect. The method provided by the invention is implemented through the following process: using two circulations to realize the dynamic interference suppression, wherein the internal circulation is used for completing the feature tracking of the dynamic interference, using a first i-th interference feature vector wi(t-1) at a t-1 moment and receiving data X(:, t) at a t moment to obtain a feature wave-beam output yi(t) at the t moment, and then using the feature wave-beam output yi(t) at the t moment and a feature value di(t-1) at the ith dynamic interference at the t-1 moment to update a dynamic interference feature di(t) at the t moment and the interference feature vector wi(t) at the t moment; then using the interference feature vector wi(t) and the feature beam output yi(t) at the t moment to update the receiving data vector X(:, t) at the t moment; and using all dynamic interference vector wi(t) to compose a widened dynamic interference feature matrix F in an external circulation mode, estimating an anti-interference right vector h, then using the anti-interference right vector h to perform the dynamic interference suppression on the receiving data. The high-dynamic interference auto-tracking steady suppression method has obvious good interference suppression effect, and can be applied to the space dynamical interference suppression, and the output signal to interference plus noise ratio thereof is more approximate to a theoretical optimal value.

Description

High dynamic-interference auto-tracking steady suppression method

Technical field

The invention belongs to the signal processing technology field, relate to Array Signal Processing and auto-adaptive filtering technique, can be used for interference autotracking inhibition interference when the high dynamic motion in space and guarantee simultaneously signal stabilization output.

Background technology

Satellite navigation and location system can be round-the-clock, round-the-clock provides the information such as position, speed and time, in civilian and national defence field wide application demand arranged.But, because electromagnetic environment is day by day abominable and the navigation signal arrival receiver is very faint, so that navigation neceiver is extremely responsive to disturbing, this to disturbing responsive fragility to have a strong impact on the performance of navigation.It is one of main bugbear of facing of Adaptive Anti-jamming that the high dynamic disturbance that exists in the reality suppresses.Here high dynamic disturbance refers to that there are relative motion in interference source and receiver, the arrival bearing who causes interference source to arrive receiver is fast the change, for example the rapid movement of interference own is as being placed on the unmanned plane, and receiver is motionless, perhaps the receiver high-speed motion disturb as being placed on aircraft, guided missile or the satellite motionless, perhaps both motions.Conventional anti-interference method such as the sample covariance matrix time-independent static interference of arrival bearing that SMI method, least mean-square error LMS method, recurrence least square RLS method etc. all are applicable to disturb of inverting suppresses situation.They remove the impact of disturbing the signal generation by constraint or iterative step, thereby have realized extracting under the static interference background purpose of signal.But suppress for high dynamic disturbance, above method is no longer applicable, because these methods can not be followed the tracks of the feature of dynamic disturbance effectively, when the arrival bearing who disturbs changes fast, using these methods to disturb inhibition can't be in real time to form zero in the interference position of directional diagram falls into, namely do not have zero and fall into the autotracking performance, thereby make array can't distinguish signal and dynamic disturbance, cause high dynamic disturbance inhibition not good.

Summary of the invention

The object of the invention is to overcome the deficiency of above-mentioned prior art, a kind of high dynamic-interference auto-tracking steady suppression method has been proposed, with quick tracking interference radiating way the recess position of directional diagram is aimed in real time and disturbed arrival bearing, and guarantee main lobe registration signal arrival bearing, thereby realized that high dynamic disturbance suppresses to guarantee simultaneously the stable output of array.

For achieving the above object, technical scheme of the present invention comprises the steps:

1. to the aerial array digital sample, obtain a collection of receive data X that comprises signal and dynamic disturbance, wherein X is that M * N ties up matrix, and M is the array element number of array, and N is the data sampling number;

2. adopt inside and outside two docking of recirculating to receive that dynamic disturbance suppresses among the data X:

1) establish outer circulation variable t=1, t represents sampling instant, the eigenwert of i dynamic disturbance of initialization: d _i(t-1)=0, i=1,2 ..., r, r are the dynamic disturbance numbers, the proper vector w of i dynamic disturbance of initialization _i(t-1) for being that all the other elements are that column vector is tieed up in 0 M * 11 except i element;

2) establish interior loop variable i=1, i represents the dynamic disturbance sequence number;

3) with t-1 moment i interference characteristic vector w _i(t-1) and t constantly receive data X (:, t) obtain constantly eigen beam output of t:

Wherein H represents conjugate transpose;

4) with constantly eigen beam output of t y _i(t) and the t-1 eigenwert d of i dynamic disturbance constantly _i(t-1) upgrade t dynamic disturbance eigenwert constantly: d _i(t)=(1-α+α β) d _i(t-1)+and α | y _i(t) | ², wherein α is smoothing factor, β is forgetting factor, with t dynamic disturbance eigenwert d constantly _i(t) upgrade constantly dynamic disturbance proper vector of t:

$w_i\left(t\right)=w_i(t-1)+\mathrm{\α}[X(:,t)-w_i(t-1)y_i\left(t\right)]\frac{y_i^{*}\left(t\right)}{d_i\left(t\right)},$ Wherein * represents conjugation;

5) with t moment interference characteristic vector w _i(t) upgrade t constantly receive data vector X (:, t)=X (:, t)-w _i(t) y _i(t), loop variable i=i+1 in upgrading is if the interior loop variable i after upgrading then is back to step 3 less than or equal to dynamic disturbance number r) continue circulation in the execution, otherwise execution in step 6), finish t constantly to r signature tracking that disturbs;

6) when outer circulation variable t can be divided exactly the hits T of piecemeal processing, execution in step 7) to 9), otherwise skip to step 10);

7) utilize r dynamic disturbance proper vector w _i(t) composition is widened dynamic disturbance eigenmatrix: F=[w ₁(t), Bw ₁(t) ..., w _r(t), Bw _r(t)], B is the diagonal matrix that forms with each array element coordinate:

B=diag (dx ₁, dx ₂..., dx _M), dx wherein _m, m=1,2 ..., M represents m array element coordinate;

8) estimate anti-dynamic disturbance weight vector according to widening the dynamic disturbance eigenmatrix:

$h={\mathrm{Pa}}_s/\sqrt{\left({a_s}^H{\mathrm{Pa}}_s\right)}$

Wherein P is by the orthogonal complement space of widening the interference characteristic matrix construction: P=I _M-F (F ^HF) ^-1F ^H, I _MThat M * M ties up unit matrix, a _sIt is M * 1 dimensional signal steering vector;

9) obtain anti-dynamic disturbance output by anti-dynamic disturbance weight vector h:

z＝h ^HX(：，t+T+1：t+2T)；

10) upgrade outer circulation variable t=t+1, then be back to step 2 if the outer circulation variable t after upgrading counts N less than or equal to data sampling), otherwise finish outer circulation, finish the inhibition to dynamic disturbance among the receive data X this moment.

The present invention compared with prior art has the following advantages:

(a) the present invention is owing to having utilized smoothing processing to upgrade t dynamic disturbance eigenwert d constantly _i(t) and corresponding proper vector w _i(t), guaranteed the arrival bearing of the main lobe registration signal of directional diagram, recess is aimed at the arrival bearing of dynamic disturbance in real time, and the signature tracking that makes it disturbing is more accurate.

(b) the present invention is owing to using interference characteristic vector w _i(t) and diagonal matrix B form dynamic disturbance eigenmatrix F, it has been widened and disturbs in the spatial domain locational zero to fall into, and makes it more obvious to the dynamic disturbance inhibition.

Simulation result shows: the present invention and the sample covariance matrix SMI method of inverting is compared, because above advantage of the present invention has improved array output Signal to Interference plus Noise Ratio, makes its inhibition dynamic disturbance have more sane performance.

Description of drawings

Fig. 1 is the used aerial array layout viewing of the embodiment of the invention;

Fig. 2 is the process flow diagram of the inventive method;

Fig. 3 is the directional diagram when having a dynamic disturbance among the receive data X;

Fig. 4 is the signal spectrum figure after respectively Fig. 3 being suppressed with the present invention and existing SMI method;

Fig. 5 is the output Signal to Interference plus Noise Ratio figure after respectively Fig. 3 being suppressed with the present invention and existing SMI method;

Fig. 6 is the directional diagram when having two dynamic disturbance among the receive data X;

Fig. 7 is the signal spectrum figure after respectively Fig. 6 being suppressed with the present invention and existing SMI method;

Fig. 8 is the output Signal to Interference plus Noise Ratio figure after respectively Fig. 6 being suppressed with the present invention and existing SMI method.

Embodiment

With reference to Array Model Fig. 1 and process flow diagram 2, the step that the present invention realizes is as follows:

Step 1. pair aerial array digital sample obtains a collection of receive data X=a that comprises signal and dynamic disturbance _sS ₀+ a _iS _i+ n, the arrival bearing who establishes signal is known by direction-finding method in advance, and wherein X is that M * N ties up matrix, and M is the array element number of array, and N is the data sampling number, S ₀Be the vector that signal in the receive data forms, a _sThe signal guide vector, S _iFor disturbing the vector that forms, a in the receive data _iBe the dynamic disturbance steering vector, n is the noise in the receive data.

Step 2. adopts the inside and outside two inhibition dynamic disturbance that recirculate, and interior circulation is finished r signature tracking that disturbs among the receive data X, and outer circulation utilizes the feature of these interference to carry out the dynamic disturbance inhibition, and r is the dynamic disturbance number here:

(2.1) establish outer circulation variable t=1, t represents sampling instant, the eigenwert of i dynamic disturbance of initialization: d _i(t-1)=0, i=1,2 ..., r, the proper vector w of i dynamic disturbance of initialization _i(t-1) for being that all the other elements are that column vector is tieed up in 0 M * 11 except i element;

(2.2) establish interior loop variable i=1, i represents the dynamic disturbance sequence number;

(2.3) with t-1 moment i interference characteristic vector w _i(t-1) and t constantly receive data X (:, t) obtain constantly eigen beam output of t: Wherein H represents conjugate transpose;

(2.4) with constantly eigen beam output of t y _i(t) and the t-1 eigenwert d of i dynamic disturbance constantly _i(t-1) upgrade t dynamic disturbance eigenwert constantly: d _i(t)=(1-α+α β) d _i(t-1)+and α | y _i(t) | ², wherein α is smoothing factor, β is forgetting factor, with t dynamic disturbance eigenwert d constantly _i(t) upgrade constantly interference characteristic vector of t:

Wherein * represents conjugation;

(2.5) with t moment interference characteristic vector w _i(t) upgrade t constantly receive data vector X (:, t)=X (:, t)-w _i(t) y _i(t), loop variable i=i+1 in upgrading continues interior circulation if the interior loop variable i after upgrading, then is back to step (2.3) less than or equal to dynamic disturbance number r, otherwise execution in step (2.6) is finished t constantly to r signature tracking that disturbs;

(2.6) adopt the method for minute fast deal with data, when outer circulation variable t can be divided exactly piecemeal hits T, execution in step (2.7) was to (2.9), otherwise skipped to step (2.10);

(2.7) with r dynamic disturbance proper vector w _i(t) composition is widened dynamic disturbance eigenmatrix: F=[w ₁(t), Bw ₁(t) ..., w _r(t), Bw _r(t)], B is the diagonal matrix that forms with each array element coordinate: B=diag (dx ₁, dx ₂..., dx _M), dx wherein _m, m=1,2 ..., M represents m array element coordinate;

(2.8) estimate anti-dynamic disturbance weight vector according to widening the dynamic disturbance eigenmatrix:

$h={\mathrm{Pa}}_s/\sqrt{\left({a_s}^H{\mathrm{Pa}}_s\right)}$

Wherein P is by the orthogonal complement space of widening the interference characteristic matrix construction: P=I _M-F (F ^HF) ^-1F ^H, I _MThat M * M ties up unit matrix, a _sIt is the signal guide vector;

(2.9) obtain anti-dynamic disturbance output Z by anti-dynamic disturbance weight vector h:

Z＝h ^HX(：，t+T+1：t+2T)

Wherein t is the outer circulation variable, and T is the piecemeal hits;

(2.10) upgrade outer circulation variable t=t+1, then be back to step (2.2) if the outer circulation variable t after upgrading counts N less than or equal to data sampling, otherwise finish outer circulation, finish the inhibition to dynamic disturbance among the receive data X this moment.

(1) experimental situation

The present invention adopts the even sensor array of linearity of n=8, and the signal carrier frequency is F _c=10 ⁹Hz, the distance between the adjacent sensors element is half wavelength lambda/2, and it is 1024 that data sampling is counted N, and the hits T that piecemeal is processed is 16, and smoothing factor α is 0.5, forgetting factor β is 0.92.

(2) experiment content and result

Experiment 1 is to existing dried making an uproar than being the dynamic disturbance of 40dB, its arrival bearing θ among the receive data X ₁(t)=and 20+0.01t °/s, the signal to noise ratio (S/N ratio) of signal is 0dB among the receive data X, its arrival bearing is that 0 ° receive data utilizes smoothing processing to upgrade t dynamic disturbance eigenwert d constantly _i(t) and corresponding proper vector w _i(t), draw the directional diagram of this dynamic disturbance and the respective direction figure comparison that draws with employing SMI method, its result as shown in Figure 3; Then estimate 1 anti-interference weight vector h every 15 secondary data sampling numbers, acting on array received data X with anti-interference weight vector h again draws X to received signal and disturbs signal spectrum figure after suppressing, and suppressing the signal spectrum figure contrast of this interference with adopting the SMI method, its result is as shown in Figure 4; The output Signal to Interference plus Noise Ratio of array after suppressing to disturb with the inventive method and SMI method statistic respectively at last, its result as shown in Figure 5.

As seen from Figure 3, use the present invention can make 0 ° of the main lobe registration signal arrival bearing of directional diagram, and produce at least at interference radiating way-zero the falling into of 60dB, and the SMI method is so that major lobe of directional diagram skew, zero of interference falls into and reaches most-40dB.This has illustrated that the present invention has guaranteed the arrival bearing of the main lobe registration signal of directional diagram, and can produce darker zero falling at interference radiating way.

As can be seen from Figure 4, adopt the inventive method to carry out after the dynamic disturbance inhibition, signal amplitude is 68dB, interference magnitude is 31dB, and the difference of the two is 37dB, and adopts the SMI method to disturb after the inhibition, signal amplitude is 60dB, and interference magnitude is 48dB, and the difference of the two is 12dB.Signal interference ratio increased relatively after this explanation adopted the inventive method to suppress high dynamic disturbance.It can also be seen that from Fig. 4, disturb afterwards interference spectrum appearance on every side of inhibition not resist the frequency line component that falls with the SMI method, illustrate that the inventive method anti-jamming effectiveness is better.

Fig. 5 further illustrates the superiority of the method.Here show that two kinds of methods export Signal to Interference plus Noise Ratio accordingly.The output Signal to Interference plus Noise Ratio that can find out the inventive method is on average about 8.5dB, and near theoretical optimal value 10 * log10 (8) ≈ 9dB, and the output Signal to Interference plus Noise Ratio of SMI method is on average about-1dB, and this has illustrated that this method has more stable output.

Experiment 2, to there being two dynamic disturbance among the receive data X, one of them is above-mentioned interference θ ₁(t), another is that arrival bearing is θ ₂(t)=-30 °/s of 5sin (π t/500), dried making an uproar than being the dynamic disturbance of 30dB, the signal to noise ratio (S/N ratio) of signal still is 0dB among the receive data X, and its arrival bearing is that 0 ° receive data is continued to use above-mentioned disposal route and utilized first smoothing processing to upgrade t dynamic disturbance eigenwert d constantly _i(t) and corresponding proper vector w _i(t), draw the directional diagram of these two dynamic disturbance and the respective direction figure comparison that draws with employing SMI method, its result as shown in Figure 6; Then estimate 1 anti-interference weight vector h every 15 secondary data sampling numbers, acting on array received data X with anti-interference weight vector h again draws X to received signal and disturbs signal spectrum figure after suppressing, and suppressing the signal spectrum figure contrast of these two interference with adopting the SMI method, its result is as shown in Figure 7; The output Signal to Interference plus Noise Ratio of array after suppressing to disturb with the inventive method and SMI method statistic respectively at last, its result as shown in Figure 8.

As can be seen from Figure 6, the inventive method can be respectively each interference radiating way formation-50dB and-zero the falling into of 60dB, make simultaneously main lobe aim at arrival bearing.

As shown in Figure 7, suppressing two method of SMI when disturbing anti-jamming effectiveness not as good as the inventive method, because find out that from spectrogram all there is the not suppressed component that falls in two interference, and there is not this phenomenon in our rule.

Export as seen from Figure 8 Signal to Interference plus Noise Ratio on average about 8dB, and the output Signal to Interference plus Noise Ratio of SMI method is on average at-3dB.

In sum, employing smoothing processing and zero method that falls into of widening suppress high dynamic motion interference can make the recess of directional diagram aim in real time the arrival bearing of dynamic disturbance, guarantee simultaneously the arrival bearing of main lobe registration signal, compare SMI method interference suppressioning effect obvious, the output Signal to Interference plus Noise Ratio is near theoretical optimal value.

Claims (1)

1. a high dynamic-interference auto-tracking steady suppression method comprises the steps:

(1) to the aerial array digital sample, obtain a collection of receive data X that comprises signal and dynamic disturbance, wherein X is that M * N ties up matrix, and M is the array element number of array, and N is the data sampling number;

(2) adopt inside and outside two docking of recirculating to receive that dynamic disturbance suppresses among the data X:

(2a) establish outer circulation variable t=1, t represents sampling instant, the eigenwert of i dynamic disturbance of initialization: d _i(t-1)=0, i=1,2 ..., r, r are the dynamic disturbance numbers, the proper vector w of i dynamic disturbance of initialization _i(t-1) for being that all the other elements are that column vector is tieed up in 0 M * 11 except i element;

(2b) establish interior loop variable i=1, i represents the dynamic disturbance sequence number;

(2c) with t-1 moment i interference characteristic vector w _i(t-1) and t constantly receive data X (:, t) obtain constantly eigen beam output of t: Wherein H represents conjugate transpose;

(2d) with constantly eigen beam output of t y _i(t) and the t-1 eigenwert d of i dynamic disturbance constantly _i(t-1) upgrade t dynamic disturbance eigenwert constantly: d _i(t)=(1-α+α β) d _i(t-1)+and α | y _i(t) | ², wherein α is smoothing factor, β is forgetting factor, with t dynamic disturbance eigenwert d constantly _i(t) upgrade constantly interference characteristic vector of t: $w_i\left(t\right)=w_i(t-1)+\mathrm{\α}[X(:,t)-w_i(t-1)y_i\left(t\right)]\frac{y_i^{*}\left(t\right)}{d_i\left(t\right)},$ Wherein * represents conjugation;

(2e) with t moment interference characteristic vector w _i(t) upgrade t constantly receive data vector X (:, t)=X (:, t)-w _i(t) y _i(t), loop variable i=i+1 in upgrading continues interior circulation if the interior loop variable i after upgrading, then is back to step (2c) less than or equal to dynamic disturbance number r, otherwise execution in step (2f) is finished t constantly to r signature tracking that disturbs;

(2f) when outer circulation variable t can be divided exactly the hits T of piecemeal processing, execution in step (2g)-(2i), otherwise skip to step (2j);

(2g) utilize r dynamic disturbance proper vector w _i(t) composition is widened dynamic disturbance eigenmatrix: F=[w ₁(t), Bw ₁(t) ..., w _r(t), Bw _r(t)], B is the diagonal matrix that forms with each array element coordinate: B=diag (dx ₁, dx ₂..., dx _M), dx wherein _m, m=1,2 ..., M represents m array element coordinate;

(2h) estimate anti-dynamic disturbance weight vector according to widening the dynamic disturbance eigenmatrix:

$h={\mathrm{Pa}}_s/\√\sqrt{\left({a_s}^H{\mathrm{Pa}}_s\right)}$

Wherein P is by the orthogonal complement space of widening the interference characteristic matrix construction: P=I _M-F (F ^HF) ^-1F ^H, I _MThat M * M ties up unit matrix, a _sM * 1 dimensional signal steering vector, () ^-1Representing matrix inversion operation symbol;

(2i) obtain anti-dynamic disturbance output by anti-dynamic disturbance weight vector h:

z＝h ^HX(:，t+T+1:t+2T)

(2j) upgrade outer circulation variable t=t+1, then be back to step (2b) if the outer circulation variable t after upgrading counts N less than or equal to data sampling, otherwise finish outer circulation, finish the inhibition to dynamic disturbance among the receive data X this moment.

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