scholarly journals On Time Compression Overlap-Add Technique in Linear Frequency Modulation Pulse Compression Radar Systems: Design and Performance Evaluation

IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 27525-27537 ◽  
Author(s):  
Ahmed Youssef ◽  
Peter F. Driessen ◽  
Fayez Gebali ◽  
Belaid Moa

A lot of applications in radar systems necessitate low range side-lobe performance which is achieved by pulse compression processing. Linear Frequency Modulation (LFM) signal is mainly used chirp signal for this processing. The paramount drawback in LFM is the first side-lobe level of -13dB at the receiver side. In this paper, LFM signal is modified by using simple two-stage piece wise linear frequency modulation (PWLFM) functions. The autocorrelation function of this PWLFM signal exhibited low peak sidelobe level ratio (PSLR) value compared to its counterpart LFM signal. An attempt is made to further reduce the side lobe values by using novel Convolutional windows. The simulation results confirm a significant side lobe reduction by the LFM signal designed using PWLFM functions when a more flexible Power of Cosine window function is applied compared to all other window functions.


2020 ◽  
Vol 13 (44) ◽  
pp. 4465-4473
Author(s):  
Chandu Kavitha ◽  

Background/Objectives: The design of appropriate Non-Linear Frequency Modulation (NLFM) signals continues to be the focus of research in radar pulse compression theory for sidelobe reduction. This study focuses on a heuristic design and optimization algorithm to optimize the side lobe values of the NLFM signal designed using two-piece wise linear frequency modulation (LFM) functions. Methods: 1) Heuristic search identifies the optimum B1, T1, and B2, T2, which yield the lowest sidelobe value of the designed function.2) Compute all the side lobe values of the designed NLFM signal using an algorithm developed in Python scripting language. To plot a complete contour map for all the calculated side lobe values, which helps identify the associated variations in the range of side lobe values. Finally, optimize the side lobe values keeping the main lobe width and time-bandwidth (BT) product unchanged by designing a dynamic optimization algorithm. Findings: The algorithm developed considered all side lobe levels after the main lobe for optimization. The focus is mainly on the peak sidelobe ratio (PSLR) value without affecting the other parameters. The results demonstrate that the achieved side lobes exhibit their desired levels. Novelty: The method is useful in all types of hardware associated with weather radar applications to military solutions. The technique can be extended to other multistage signals consisting of piecewise linear Segments. Keywords: Contour; LFM; NLFM; optimization; PSLR


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