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August  2009, 3(3): 465-486. doi: 10.3934/ipi.2009.3.465

Perfect and almost perfect pulse compression codes for range spread radar targets

1. 

University of Oulu, Sodankylä Geophysical Observatory, Sodankylä, Finland

2. 

Washera Geospace and Radar Science Laboratory, Bahir Dar University, P.O.Box, 79, Bahir Dar, Gojjam, Ethiopia

3. 

Department of Mathematics and Statistics, University of Helsinki, FI-00014, Helsinki, Finland

4. 

Sodankylä Geophysical Observatory, University of Oulu, Tähteläntie 62, FIN-99600 Sodankylä, Finland

Received  October 2008 Revised  February 2009 Published  July 2009

It is well known that a matched filter gives the maximum possible output signal-to-noise ratio (SNR) when the input is a scattering signal from a point like radar target in the presence of white noise. However, a matched filter produces unwanted sidelobes that can mask vital information. Several researchers have presented various methods of dealing with this problem. They have employed different kinds of less optimal filters in terms of the output SNR from a point-like target than that of the matched filter. In this paper we present a method of designing codes, called perfect and almost perfect pulse compression codes, that do not create unwanted sidelobes when they are convolved with the corresponding matched filter. We present a method of deriving these types of codes from any binary phase radar codes that do not contain zeros in the frequency domain. Also, we introduce a heuristic algorithm that can be used to design almost perfect codes, which are more suitable for practical implementation in a radar system. The method is demonstrated by deriving some perfect and almost perfect pulse compression codes from some binary codes. A rigorous method of comparing the performance of almost perfect codes (truncated) with that of perfect codes is presented.
Citation: Markku Lehtinen, Baylie Damtie, Petteri Piiroinen, Mikko Orispää. Perfect and almost perfect pulse compression codes for range spread radar targets. Inverse Problems & Imaging, 2009, 3 (3) : 465-486. doi: 10.3934/ipi.2009.3.465
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