According to pulse-compression radar theory, the sidelobe reduction using nonlinear frequency modulation (NLFM) signal processing represents a major and present research direction. Although in literature a lot of techniques to design efficient NLFM waveforms are indicated, one of the most important methods as application area is focused on stationary phase technique (SPT) use. Consequently, the main objective of this paper is to make an extended comparative study as sidelobe suppression among some very promising NLFM laws achieved by applying of a proper SPT synthesis algorithm. In addition, some aspects related to the suitable choice of the parameters involved in the synthesis process of NLFM signals are also indicated.
It is well known that in the pulse-compression radar theory, the sidelobe reduction using synthesis of some proper nonlinear FM (NLFM) laws represents a major research direction. In order to assure the sidelobe suppression, the main objective of this paper is to present an adequate synthesis algorithm of NLFM signals based on stationary phase principle. The achieved experimental results confirm a significant sidelobe reduction (i.e., more than −40 dB) without necessity to apply some weighting techniques. In addition, the analysis of the synthesized NLFM laws by ambiguity function tool is also discussed.
One of the most recent technique to design an efficient ATR system is to use high-resolution radar (HRR) imagery as input information flow. To increase the quality of such system, an interesting approach is to use powerful artificial neural networks inside of its recognition chain. Consequently, an improved neural recognition function based on modified feature extraction and selection methods and respectively, on genetic optimized RBF network architecture is described. Finally, to confirm the broached theoretical aspects, a real HRR image database was also used.
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