Name
Title | ||
|---|---|---|
Radar clutter classification using autoregressive modelling, K-distribution and neural network |
Abstract | ||
|---|---|---|
This paper is concerned with the classification of radar returns including sea, ground and composite clutters. We first present an analysis of radar clutter recorded data allowing to validate the K amplitude distribution and the autoregressive modelling of the spectrum. Then, we briefly describe a classifier based on a multi-layer neural network. The inputs of which are the shape parameter of the K-distribution, the magnitude and the phase of the poles and the reflection coefficients calculated by means of the Burg's or multi-segment algorithm. Experimental results are presented to illustrate the performance of the proposed classifier |
Year | DOI | Venue |
|---|---|---|
1995 | 10.1109/ICASSP.1995.480091 | Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference |
Keywords | Field | DocType |
autoregressive processes,multilayer perceptrons,radar clutter,radar computing,radar signal processing,spectral analysis,statistical analysis,Burg's algorithm,K amplitude distribution,K-distribution,autoregressive modelling,composite clutter,experimental results,ground clutter,inputs,multilayer neural network,multisegment algorithm,pole magnitude,pole phase,radar clutter analysis,radar clutter classification,radar returns classification,reflection coefficients,sea clutter,shape parameter,spectral parameters | Radar,Autoregressive model,Magnitude (mathematics),K-distribution,Pattern recognition,Clutter,Computer science,Shape parameter,Artificial intelligence,Classifier (linguistics),Artificial neural network | Conference |
Volume | ISSN | ISBN |
3 | 1520-6149 | 0-7803-2431-5 |
Citations | PageRank | References |
1 | 0.38 | 2 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bouvier, C. | 1 | 1 | 0.38 |
| Martinet, L. | 2 | 1 | 0.38 |
| Favier, G. | 3 | 2 | 1.48 |
| Sedano, H. | 4 | 1 | 0.38 |