Universal two-channel STAP filter

• US 6,563,455 B2
• Filed: 07/23/2001
• Issued: 05/13/2003
• Est. Priority Date: 07/21/2000
• Status: Expired due to Fees

• Current Assignee: EADS Deutschland GmbH (Airbus SE)
• Original Assignee: EADS Deutschland GmbH (Airbus SE)
• Inventors: Bickert, Bernhard, Meyer-Hilberg, Jochen
• Primary Examiner(s): Tarcza, Thomas H.
• Assistant Examiner(s): ALSOMIRI, ISAM A
• Application Number:
  US09/910,002
• Publication Number:
  US 20020044083A1
• Time in Patent Office: 659 Days
• Field of Search: 342/378, 342/380-384, 342/145, 342/168, 342/175, 342/189, 342/194
• US Class Current: 342/175
• CPC Class Codes: G01S 13/5244 Adaptive clutter cancellation specially adapted for airborne MTI, G01S13/5242
• CPC Class Codes: G01S 7/295 Means for transforming co-ordinates or for evaluating data, e.g. using computers

Abstract

To suppress interfering stationary targets in radar source data, a STAP filtering method is used. Filtering coefficients are determined, and filtering of the data takes place, in the frequency domain; the process is therefore limited to a few computing operations per matrix element of the range/Doppler matrix. Since, by means of the STAP filter according to the invention, the optimal filtering characteristics can be implemented, the stationary target suppression also functions in the range of the minor lobes of the antenna. Therefore, data of individual adjacent channels (L/R, left/right) can be processed as well as summation and difference signals (Σ/Δ).

Claims

1. A method of filtering radar source data comprising distance Doppler matrices X₁ and X₂ of two receiving channels, by Space-Time Adaptive Processing (STAP), wherein the data of the distance/Doppler matrices X₁ and X₂ of individual adjacent channels (left/right) as well as of sum and difference signals (Σ

/Δ

) are processed according to the same procedure, and wherein both computation of filter coefficients α

(i) and β

(i), and filtering take place in the frequency domain, said method comprising;

determining auto-correlations r₁₁ and r₂₂ and cross-correlations r₁₂ of the signals X₁ and X₂ of both receiving channels, according to the following equations;

$r_{11}<br><br>\left(i\right)=\underset{j=1}{\overset{N_{\mathrm{RG}}}{\sum <br><br>}}<br><br>X_1<br><br>\left(i,j\right)·<br><br>X_1^{*}<br><br>\left(i,j\right)$$r_{22}<br><br>\left(i\right)=\underset{j=1}{\overset{N_{\mathrm{RG}}}{\sum <br><br>}}<br><br>X_2<br><br>\left(i,j\right)·<br><br>X_2^{*}<br><br>\left(i,j\right)$$r_{12}<br><br>\left(i\right)=\underset{j=1}{\overset{N_{\mathrm{RG}}}{\sum <br><br>}}<br><br>X_1<br><br>\left(i,j\right)·<br><br>X_2^{*}<br><br>\left(i,j\right)$

wherein X₁ (i, j) is a complex range/Doppler matrix of a first of the two channels, X₂ (i, j) is a complex range/Doppler matrix of a second of the two channels, N_DZ is a number of Doppler cells, N_RG is a number of range gates, and 1≦

i≦

N_DZ;

determining whether the first channel has the better signal-to-noise ratio according to the following condition $\frac{\max <br><br>\left(r_{11}<br><br>\left(i\right)|1\le <br><br>i\le <br><br>N_{\mathrm{DZ}}\right)}{\underset{i=1}{\overset{N_{\mathrm{DZ}}}{\sum <br><br>}}<br><br>r_{11}<br><br>\left(i\right)}><br><br>\frac{\max <br><br>\left(r_{22}<br><br>\left(i\right)|1\le <br><br>i\le <br><br>N_{\mathrm{DZ}}\right)}{\underset{i=1}{\overset{N_{\mathrm{DZ}}}{\sum <br><br>}}<br><br>r_{22}<br><br>\left(i\right)};<br><br>$

applying a selection rule which provides that if the first channel has the better signal-to-noise ratio, the filtering coefficients a (i) and b (i) are determined according to

2. The method according to claim 1, wherein a deviation takes place from the selection rule, when the channel with the poorer signal-to-noise ratio (S/N) clearly has less signal output in comparison to the better channel.

3. The method according to claim 1, wherein correlation values of respective adjacent Doppler cells are used to determine a mean.