normsig.m

阵列信号处理的工具箱

function sigOut = normsig(sigIn, method, noSrc, checkParamFlag)

%NORMSIG Normalizes a radar signal or a spatial correlation matrix relative the noise power.
%
%--------
%Synopsis:
%  sigOut = normsig(sigIn)
%  sigOut = normsig(sigIn,[],noSrc)
%
%Description:
%  Normalizes a radar signal (RxRadarSigT) or a spatial correlation matrix 
%  (RxCorrMatT) relativ the noise power for each trial, cpi, and range.
%  The noise power is estimated as the mean value of the smallest eigenvalues 
%  (the noise eigenvalues) of the spatial correlation matrix.
%
%  For radar signals, the same normalization constant is applied to all
%  channels and all pulses.
%
%Output and Input:
%  sigOut  (RxRadarSigT) : Radar signal after normalization.
%    If the input parameter is of type RxRadarSigT so will this output be.
%  sigOut  (RxCorrMatT) : Spatial correlation matrix after normalization.
%    If the input parameter is of type RxCorrMatT so will this output be.
%
%  sigIn   (RxRadarSigT) : Radar signal before normalization.
%  sigIn   (RxCorrMatT) : Spatial correlation matrix before normalization.
%  noSrc [D](IntScalarT): Number of signal sources. This means that there
%    are ((number-of-channels) - noSrc) noise eigenvalues. If this value
%    is too low, the estimated noise power will be somewhat too low. If
%    this value is too high, the estimated noise power will be too high
%    (maybe much too high). Default value is = 1, which means that only the
%    smallest eigenvalue is used.
%  checkParamFlag [D] (BoolT): 0 = Do not check data types of input parameters.
%    1 = Check data types of input parameters (default).
%
%--------
%Notations:
%  Data type names are shown in parentheses and they start with a capital
%  letter and end with a capital T. Data type definitions can be found in [1]
%  or by "help dbtdata".
%  [D] = This parameter can be omitted and then a default value is used.
%  When the [D]-input parameter is not the last used in the call, it must be
%  given the value [], i.e. an empty matrix.
%  ... = There can be more parameters. They are explained under respective
%  metod or choice.
%
%Examples:
%
%Software Quality:
%  (About what is done to ascertain software quality. What tests are done.)
%
%Known Bugs:
%
%References:
%  [1]: Bj鰎klund S.: "DBT, A MATLAB Toolbox for Radar Signal Processing.
%    Reference Guide", FOA-D--9x-00xxx-408--SE, To be published.
%
%See Also:
%  basecorrm, ecorrm

%   *  DBT, A Matlab Toolbox for Radar Signal Processing  *
% (c) FOA 1994-2000. See the file dbtright.m for copyright notice.
%
%  Start        : 990504 Svante Bj鰎klund (svabj).
%  Latest change: $Date: 2000/10/16 15:21:13 $ $Author: svabj $.
%  $Revision: 1.9 $
% *****************************************************************************


% ----------------------------------------------------------------------- %
% Handle input parameters
% ----------------------------------------------------------------------- %

arginNo=1;
if (nargin < arginNo)
  error('DBT-Error: To few input parameters.')
end
arginNo = arginNo +1;


% ****************** Add missing input parameters ******************

if (nargin < arginNo)
  method = [];
end
arginNo = arginNo +1;
if (nargin < arginNo)
  noSrc = [];
end
arginNo = arginNo +1;
if (nargin < arginNo)
  checkParamFlag = [];
end
arginNo = arginNo +1;


% ****************** Default values ******************

if isempty(method)
  method = [];
end%if
if isempty(noSrc)
  noSrc = [];
end%if
if isempty(checkParamFlag)
  checkParamFlag = 1;
end%if


% ****************** Error check input parameters ******************

if (checkParamFlag)
  chkdtype(sigIn, 'RxRadarSigT','RxCorrMatT')
end%if

% ****************** Create output variable ******************

sigOut = sigIn;


% ----------------------------------------------------------------------- %
% RxRadarSigT: Radar signals.
% ----------------------------------------------------------------------- %

if (strcmp(sigIn.dataType,'RxRadarSigT'))

  % ****************** Signal size ******************

  sizeSpec = sizem(sigIn.signals);
  noPulses = sizeSpec(1);	
  noRanges = sizeSpec(2);
  noChannels = sizeSpec(3);
  noExtras = sizeSpec(4);
  noCPIs   = sizeSpec(5);
  noTrials = sizeSpec(6);

  if isempty(noSrc)
    noSrc = noChannels-1;
      % Default value: use only the smallest eigenvalue.
  end%if



  % ****************** Loops ******************

  for trialLoop = 1:noTrials
    for cpiLoop = 1:noCPIs
      for extraLoop = 1:noExtras
        for rangeLoop = 1:noRanges
          %sigMat=sigIn.signals(:,rangeLoop, :, extraLoop, cpiLoop, trialLoop);
          sigMat = getm3(sigIn.signals, 3, [], ':',rangeLoop, ':', ...
            extraLoop, cpiLoop, trialLoop);
          corrMatMx = (1/noPulses) * sigMat*sigMat';
            % Estimate spatial correlation matrix. Use all pulses as samples.
          eigVals = (flipud(sort(abs(eig(corrMatMx)))));
            % Calculate eigenvalues of the spatial correlation matrix.
          %noisePower = eigVals(noChannels);
          noisePower = mean(eigVals(noSrc+1:noChannels));
            % Choose the mean value of the smallest eigenvalues as an
            % estimate of the noise power.
          sigOut.signals(:,rangeLoop,:,extraLoop,cpiLoop,...
            trialLoop) = sigOut.signals(:,rangeLoop,:,extraLoop,cpiLoop,...
            trialLoop) / sqrt(noisePower);
            % Normalize the signal to the noise amplitude.
        end%for rangeLoop
      end%for extraLoop
      infoStr = sprintf('normsig: cpiLoop = %d(%d), rangeLoop = %d(%d)\r',...
        cpiLoop, noCPIs, rangeLoop, noRanges);
      dbtinfo(infoStr,1);
    end%for cpiLoop
    dbtinfo('');	%New line.
  end%for trialLoop


% ----------------------------------------------------------------------- %
% RxCorrMatT: Correlation matrices.
% ----------------------------------------------------------------------- %
elseif (strcmp(sigIn.dataType,'RxCorrMatT'))

  % ****************** Correlation matrix size ******************
  sizeSpec = sizem(sigIn.corrMat);
  noChannels = sizeSpec(1);
  %noPulses = 1;	
    % Can only store correlation matrix for a single pulse in RxCorrMatT data 
    % type.
  noRanges = sizeSpec(3);
  noExtras = sizeSpec(4);
  noCPIs   = sizeSpec(5);
  noTrials = 1;
    % Can only store correlation matrix for a single trial in RxCorrMatT data 
    % type.

  if isempty(noSrc)
    noSrc = noChannels-1;
      % Default value: use only the smallest eigenvalue.
  end%if


  % ****************** Loops ******************

  for trialLoop = 1:noTrials
    for cpiLoop = 1:noCPIs
      for extraLoop = 1:noExtras
        for rangeLoop = 1:noRanges
          corrMatMx = sigIn.corrMat(:,:,rangeLoop, extraLoop, cpiLoop);
          [U,S,V] = svd(corrMatMx);
            % Calculate eigenvalues of the spatial correlation matrix.
          eigVals = diag(S);
          noisePower = mean(eigVals(noSrc+1:noChannels));
            % Choose the mean value of the smallest eigenvalues as an
            % estimate of the noise power.
          %eigVals = eigVals / (noisePower);
          %corrMatMx = U*diag(eigVals)*V';
          corrMatMx = corrMatMx ./ (noisePower);
            % Normalize the correlation matrix to the noise power.
            % This could also be done by: corrMatMx =  corrMatMx ./ noisePower;
          sigOut.corrMat(:,:,rangeLoop, extraLoop, cpiLoop) = corrMatMx;
        end%for rangeLoop
      end%for extraLoop
      infoStr = sprintf('normsig: cpiLoop = %d(%d), rangeLoop = %d(%d)\r',...
        cpiLoop, noCPIs, rangeLoop, noRanges);
      dbtinfo(infoStr,1);
    end%for cpiLoop
    dbtinfo('');	%New line.
  end%for trialLoop


else
  error('DBT-Error: Illegal datatype of input parameter "inData".')
end%if