CN104808219B - Novel space-time joint anti-interference method - Google Patents

Abstract

The invention relates to a space-time array antenna anti-interference method in satellite navigation equipment, in particular to a novel space-time joint anti-interference method. The space-time joint anti-interference method comprises the following steps of restraining narrow-band interference in a navigation signal direction through the improved frequency domain narrow-band interference filter-out technology and achieving iteration solution of space-time array weight in combination with minimum variable step size mean square error to reduce the algorithm complexity of the method. The space-time array antenna anti-interference method in the satellite navigation equipment can restrain interference in the navigation signal direction, is low in algorithm complexity, simple in achievement and particularly suitable for application of future mini-sized high-dynamic anti-interference terminals.

Description

A kind of new space-time joint anti-interference method

Technical field

The present invention relates to a kind of space-time array Antenna Anti-jamming method on satellite navigation, more particularly, to based on elder generation The arrowband filtered using frequency domain filtering method on navigation signal direction is disturbed, and recycles Variable Step Algorithm to ask for space-time two-dimensional power arrow The satellite navigation signals anti-interference method of amount, specially a kind of new space-time joint anti-interference method.

Background technology

With the increasingly complexity of satellite navigation application electromagnetic space environment, what navigation terminal precision positioning also became is increasingly stranded Difficulty, various navigation terminals suppress perturbation technique and produce therewith.Traditional receiver Anti-Jamming Technique has spatial domain filtering technique, time domain There is certain defect in performance in filtering technique and frequency domain filtering technology, these Anti-Jamming Techniques.Space-time adaptive treatment In the case where array element is not increased, suppressible interference number is greatly increased technology, and with the treatment interference in broadband Ability, so that the antijamming capability of receiver has the raising of matter.

At present, the key point of space-time Anti-Jamming Technique is the implementation method that space-time weight vector is solved.What weight vector was solved General flow figure is as schemed shown in (1).Increase equal number of delay tap in each array element of array antenna, so as to form sky Shi Erwei Combined Treatment structures, from from the perspective of single array element, form time domain FIR structures；From the point of view of node at the same time, Form airspace filter structure.Single-frequency, arrowband, wideband interferer signal can be suppressed by space-time joint processing.

Space-time two-dimensional adaptive anti-jamming processing technology is usually using linear constraint minimal variance (LCMV) criterion, principle According to satellite-signal power well below noise and jamming power, so that spatially and temporally entering in space-time joint processing structure Row constraint makes output signal variance minimum to adjust weights, and interfering energy is weakened significantly.Response that minimum variance is undistorted (MVDR) Criterion is a kind of special case of LCMV criterions.When as satellite-signal space-time steering vector S, oneself knows, constrain on satellite-signal space-time direction Response g=1, output signal power minimum is： Best initial weights closed solution based on linearly constrained minimum variance can be expressed as:In formula, W= [ω₁₁,ω₁₂,…,ω_MP]^TIt is MP × 1 dimensional vector, M is the array number of array antenna, and P is delay cell number；R_X=E (XX^H) It is the reception signal covariance matrix of MP × MP dimensions；X=(x₁₁,x₁₂,…,x_MP)^TIt is MP × l signal vectors；S is MP × l dimensions Constrained vector.When directly carrying out weight computing using (2) formula, matrix inversion formula can be introduced, work as M, when P dimensions are larger, can obtained Preferable anti-jamming effectiveness is obtained, and increases anti-interference number.But its operand increases, big operand can cause system complex Property increase, cause the real-time of system to be deteriorated.In consideration of it, typically solving weights using recursive algorithm.

If the signal x that array element 1 is received₁N () is desired signal, i.e. d (n)=x₁(n).Then wave filter is output as：y(n) =W '^HX ', e (n)=W₁ ^HD (n)-y (n) (3), wherein W '=(ω₂₁,ω₂₂,…,ω_MP)^T, X '=(x₂₁,x₂₂,…,x_MP)^T,W₁ =[1,1 ..., 1]^T, the recurrence formula that can derive W using steepest descent method is:W_n+1'=W_n′+2μX_ne(n)^*(4),

μ is a constant, referred to as convergence factor in formula.According to formula (4), constantly iteration renewal can be obtained by best initial weights W_optEstimate Evaluation.Weights after stabilization are output as：W=[W₁ ^T,W_opt ^T]^T(5),

From the foregoing, the iterative algorithm that step-length is fixed can avoid the inversion process of matrix, so that amount of calculation is obtained substantially Reduction.But it is incompatible with steady-state error that the iterative algorithm of fixed step size can run into convergence rate in solution array weight value Problem, this can cause algorithm to decline in terms of antijamming capability.

When the direction of interference signal is identical with navigation signal, very deep null can be produced in its arrival bearing, led Navigation signal is caused seriously to be weakened.The STAP algorithms for combining IIR notch filters and space-time FIR filter are commonly used at present, can To solve the problems, such as this respect.But due to the limitation of FIR filter tap, the frequency resolution of adaptive processor is very low, Simultaneously because the frequency spectrum and statistical property of arrowband interference are unknown, therefore the method is not suitable for capturing fast-changing signal.

The content of the invention

The present invention is in order to effectively suppress to be disturbed with the equidirectional arrowband of navigation signal, it is to avoid space-time Anti-interference algorithm is calculated Process is complicated, be difficult to the shortcoming of Project Realization, there is provided a kind of new space-time joint anti-interference method.

The present invention adopts the following technical scheme that realization：A kind of new space-time joint anti-interference method, including with Lower step：

Each array element first to array received signal in per sampling all the way, then carry out radio frequency down-conversion conversion simultaneously Digitlization, obtains digitized intermediate frequency signal X_i, X_i=(x_i1, x_i2..., x_iP), i=1,2,3 ... M；

By digitized intermediate frequency signal X_iIt is input in LMS frequency domain filters, by the Frequency Domain LMS iterative algorithm in wave filter By the arrowband interference filtering in navigation signal direction, trap signal Z is obtained_i(k)=(z_i1,z_i2,…,z_iP) (i=1,2 ..., M), The frequency domain weight coefficient iterative formula of Frequency Domain LMS iterative algorithm is:U (k+1)=α U (k)+2uE (k) * F (k), wherein, U (k+ 1), U (k) is respectively the filter coefficient vector at k+1 and k moment；α is weight；μ is convergence factor；F (k) is in digitlization Frequency signal X_iFourier transformation；E (k)=F (k)-U (k) * F (k), is error signal；* it is vector dot, then Z_i(k)=f^-1 (U (K) * F (K)), wherein f^-1It is inverse Fourier transform；

By trap signal Z_iIn (k) feeding space-time array signal processing filter, arrowband broadband interference is further eliminated, should The step-length of algorithm filter more new formula is：Become The step of step-length least-mean-square error algorithm iteration goes out best initial weights be：The 2nd of Array Signal Processing wave filter arrives m-th battle array The signal that unit receives can be expressed as：Z (k)=(Z₂,Z₃,…Z_M)^H, can be expressed as after space-time array signal transacting：Y(k) =W '^HZ (k), the signal that first array element is received makees the error signal that difference obtains array element with signal Y (k) is received：E (k)= W₁ ^HZ₁(k)-Y(k)；The recurrence formula that can derive W using steepest descent method is:W_k+1'=W_k′+2μ(k)Z(k)e(k)^*, then Optimal weighting value after stabilization is W_opt, the pure navigation signal of now space-time array signal processing filter output

Improved LMS frequency domain interferences pretreatment can be on the premise of ensure navigation signal without shown in as far as possible, to the greatest extent Possible filtering is disturbed with the equidirectional arrowband of navigation signal.The signal feeding space-time array signal processing unit that will be filtered in advance, The complexity of algorithm on the premise of interference free performance is ensured, can be reduced by improved least mean square algorithm.The technology is more It is adapted to the application of following miniaturization high dynamic receiver.

Brief description of the drawings

Fig. 1 is Frequency Domain LMS Suppression of narrow band interference schematic diagram.

Fig. 2 is the anti-interference schematic diagram of traditional space-time adaptive.

Fig. 3 is the anti-interference schematic diagram of space-time adaptive of the invention.

Specific embodiment

Each array element first to array received signal in per sampling all the way, then carry out radio frequency down-conversion conversion simultaneously Digitlization, obtains digitized intermediate frequency signal X_i, X_i=(x_i1, x_i2..., x_iP), i=1,2,3 ... M；

By digitized intermediate frequency signal X_iIt is input in LMS frequency domain filters, by the Frequency Domain LMS iterative algorithm in wave filter By the arrowband interference filtering in navigation signal direction, trap signal Z is obtained_i(k), the frequency domain weight coefficient of Frequency Domain LMS iterative algorithm Iterative formula is:U (k+1)=μ E of α U (k)+2 (k) * F (k), wherein, U (k+1), U (k) is respectively the filtering system at k+1 and k moment Number vector；α is weight；μ is convergence factor；F (k) is the Fourier transformation of digitized intermediate frequency signal Xi；E (k)=F (k)- U (k) * F (k) is error signal；* it is vector dot, then Z_i(k)=f^-1(U (K) * F (K)), wherein f^-1It is inverse Fourier transform； Weight coefficient vector U (k+1) can be expressed as：U (the k+1)=μ of aU (k)+2 [1-U (k)] * F (k) * F (k), weight coefficient vector U (k+1) mathematic expectaion is represented by：E { U (the k+1) } μ of=aE { U (k) }+2 [E { ‖ F (k) ‖²}-E{U(k)‖F(k)‖²], at this In make E { ‖ F (k) ‖²}=σ², wherein σ²It is digitized intermediate frequency signal X_iPower, then E { U (k+1) }=[a-2 μ σ²]E{U(k)}+ 2μσ², therefore, U (∞) can be expressed as：Make herein ThenTherefore σ is worked as²During ＞ ＞ B, U (∞) ≈ 1, it can be seen that the effect of weights leakage factor a：To big work( On the premise of rate signal suppresses sufficiently large, the suppression to low-power level signal is greatly reduced, i.e., LMS frequency domain filters can filter out dry In the case of disturbing too big suppression will not be produced to navigation signal；

By trap signal Z_iIn (k) feeding space-time array signal processing filter, arrowband broadband interference is further eliminated, should The step-length of algorithm filter more new formula is：Become The step of step-length least-mean-square error algorithm iteration goes out best initial weights be：The 2nd of Array Signal Processing wave filter arrives m-th battle array The signal that unit receives can be expressed as：Z (k)=(Z₂,Z₃,…Z_M)^H, can be expressed as after space-time array signal transacting：Y(k) =W '^HZ (k), the signal that first array element is received makees the error signal that difference obtains array element with signal Y (k) is received：E (k)= W₁ ^HZ₁(k)-Y(k)；The recurrence formula that can derive W using steepest descent method is:W_k+1'=W_k′+2μ(k)Z(k)e(k)^*, then Optimal weighting value after stabilization is W_opt, the pure navigation signal of now space-time array signal processing filter output The algorithm utilizes the autocorrelation estimation and upper of error signal The step factor of step determines the iterative formula of step factor jointly, in the iteration starting stage, due to error function autocorrelation value compared with Greatly, the value of hyperbolic sine function is also larger, causes convergence rate faster；After iteration convergence, due to signal errors value changes Smaller, the change of step factor reduces therewith, and convergency value tends towards stability, and final wave filter exports pure navigation signal.

Claims (1)

1. a kind of new space-time joint anti-interference method, it is characterised in that comprise the following steps：

Each array element first to array received signal in per sampling all the way, then carry out radio frequency down-conversion conversion and numeral Change, obtain digitized intermediate frequency signal X_i,

X_i=(x_i1, x_i2..., x_iP), i=1,2,3 ... M；

By digitized intermediate frequency signal X_iIt is input in LMS frequency domain filters, will be led by the Frequency Domain LMS iterative algorithm in wave filter The arrowband interference filtering of sense of navigating, obtains trap signal Z_i(k)=(z_i1,z_i2,…,z_iP) (i=1,2 ..., M), frequency domain The frequency domain weight coefficient iterative formula of LMS iterative algorithms is:U (k+1)=μ E of α U (k)+2 (k) * F (k), wherein, U (k+1), U K () is respectively the filter coefficient vector at k+1 and k moment；α is weights leakage factor；μ is convergence factor；F (k) is in digitlization Frequency signal X_iFourier transformation be；E (k)=F (k)-U (k) F (k) is error signal；* it is matrix dot product, then Z_i(k)=f^-1 (U (K) * F (K)), wherein f^-1It is inverse Fourier transform；

By trap signal Z_iIn (k) feeding space-time array signal processing filter, arrowband broadband interference, the filtering are further eliminated The step-length of device algorithm more new formula is： $\left\{\begin{array}{c}\mathrm{\μ}\left(k\right)=\mathrm{\α}\tanh \left|\mathrm{\βe}\left(k\right)e(k-1)\right|\\ \mathrm{\μ}\left(k\right)=\mathrm{\α}(1-\frac{1}{(100\×e\left(k\right)e(k-1))})+\mathrm{\μ}(k-1)\end{array}\right.,$ Variable step The step of least-mean-square error algorithm iteration goes out best initial weights be：The 2nd of Array Signal Processing wave filter connects to m-th array element The signal of receipts can be expressed as：Z (k)=(Z₂,Z₃,…Z_M)^H, can be expressed as after space-time array signal transacting：Y (k)=W ‘^HZ (k), the signal that first array element is received makees the error signal that difference obtains array element with signal Y (k) is received：E (k)= W₁ ^HZ₁(k)-Y(k)；The recurrence formula that can derive W using steepest descent method is:W_k+1'=W_k′+2μ(k)Z(k)e(k)^*, then Optimal weighting value after stabilization is W_opt, the pure navigation signal of now space-time array signal processing filter output $y^{\′\left(k\right)}=e\left(k\right)={W_1}^H{Z}_1\left(k\right)-$ $W_{\mathrm{opt}}^{H}Z\left(k\right).$