Gram-schmidt space-time adaptive filter using transverse orthonormal ladder filters

Abstract

A space-time adaptive filter system is provided for eliminating unwanted signals from a radar or communication system. The filter system receives a main channel and several auxiliary channels wherein the target signal is not correlated between the various signal channels. Correlated noise components are eliminated by decorrelating the signals. The adaptive filter includes a Gram-Schmidt processor for sequentially decorrelating the auxiliary signals from the main signal. Each decorrelation element of the Gram-Schmidt processor comprises a transverse orthonormal ladder filter.

I claim: 
     
       1. In a Gram-Schmidt noise cancelation system having a plurality of individual decorrelation elements for sequentially decorrelating a main input signal from a plurality of auxiliary input signals for canceling the correlated noise components therefrom to thereby yield one filtered output signal, the improvement wherein each individual decorrelation element comprises a transverse orthonormal ladder filter. 
     
     
       2. An adaptive noise filter for receiving a plurality of input signals corresponding to the same target signal and for sequentially decorrelating said input signals to cancel the correlated noise components therefrom to thereby yield one filtered output signal, said adaptive noise filter comprising a plurality of transverse orthonormal ladder filters arranged in a Gram-Schmidt configuration for sequentially decorrelating each of said input signals from each other of said input signals to thereby yield said one filtered output signal. 
     
     
       3. An adaptive noise filter for receiving a plurality of input signals corresponding to the same target signal and for converting said plurality of input signals into one final filtered output signal vector, said noise filter comprising: N input means for receiving N input signals, X.sup.(0) n  (t), where n=1, . . . , N, each of said input signals having correlated noise components;   N memory means, MEM.sup.(m) n , where n=1, . . . , N, each for receiving and storing one of said N input signals and for producing a vector X.sup.(0) n  of time-delayed output pulses corresponding to X.sup.(0) n  (t), n=0, . . . , N-1, with said vector of output pulses X.sup.(0) n  comprising (X.sup.(0) n  (t-t d ), X.sup.(0) n  (t-2t d ), . . . ,X.sup.(0) n  (t-N n  t d ) T  ; and   N(N-1)/2 transverse orthonormal ladder filters, TOLF.sup.(m) n , m=1, . . . ,N-1, n=0, . . . ,N-1-m, arranged in N-1 levels with said mth level having N-m said transverse orthonormal ladder filters, with ladder filter TOLF.sup.(1) n  receiving X.sup.(0) n  and X.sup.(0) N-1  from said memory devices, determining the correlated components thereof, and cancelling said correlated components therefrom to produce one output X.sup.(1).sub.(n), and with each subsequent level of ladder filters TOLF.sup.(m) n , m=2, . . . ,N-1, n=0,N-1-m, receiving output vectors, X.sup.(m) n  and X.sup.(m) N-m , from a previous level, determining the correlated components thereof, and cancelling said correlated components therefrom to produce one output vector X.sup.(m-1).sub.(n), such that said N-1th level, comprising only one of said transverse orthonormal ladder filters, TOLF.sup.(N-1) n , outputs said one final filtered output signal vector, X.sup.(N-1).sub. 0.   
     
     
       4. The adaptive noise filter of claim 3, wherein each of said transverse orthonormal ladder filters receiving input X.sup.(m) n  and X.sup.(m) N-m , comprises: orthonormalization means for orthonormalizing X.sup.(m) n , with the orthonormal representation of X.sup.(m) n  denoted X'.sup.(m) n  ;   weight calculator means for calculating optimal decorrelation weights, w'.sup.(m) n , for decorrelating X'.sup.(m) n  from X.sup.(m) N-m  ; and   signal subtractor means for subtracting the product of w'.sup.(m) n  and X.sup.(m) n  from X.sup.(m) n , to thereby produce said output vector X.sup.(m+1).sub.(n).   
     
     
       5. The adaptive noise filter of claim 4, wherein said orthonormalization means comprises L two-input two-output decorrelation processors, where L is an integer ≧1. 
     
     
       6. The adaptive noise filter of claim 5, wherein, to minimize the propogation of transients within said noise filter, N n  =n(L-1)N 0 . 
     
     
       7. The adaptive noise filter of claim 5, wherein said weight calculator means calculates said optimal decorrelation weights, w'.sup.(m) n , for decorrelating X'.sup.(m) n  from X.sup.(m) N-m , by solving the equation:   R.sub.u'u' w'=r.sub.u'v,     where u'=X'.sup.(m) n , v'=X.sup.(m) N-m , R u'u'   is a L×L covariance matrix of u', and r u'v'   is the cross-covariance vector of length L between the u' and v.