Advanced Radar signal Processing Technique for better detection of slow moving smaller targets for coastal area

Abstract

Coastal surveillance is purely a technology-business. One should know what newlinekind of modern and latest technology which makes coastal security and surveillance newlinework with ease and offer true-effectiveness. Our choice of technology must be done newlinewith due precision and diligence. The principal challenge for any coastal surveillance newlineradar system is to detect small and slow-moving targets of very small Radar Cross newlineSection (RCS) in poor weather conditions including rough seas and rain. newlineConventional coastal surveillance radars suffer significant degradation in newlineperformance when it has clutter environment, making even large boats and ships newlineinvisible. Small targets such as boats, wood, fiber or rubber made components or newlineRigid Inflatable Boats (RIBs) etc. cause an asymmetric threat as it becomes highly newlinedifficult to detect them by means of conventional radar systems. Conventional marine newlineradars often suffer to detect aforesaid small targets including surface ships, low-flying newlineaircraft, icebergs, etc. Undeniably, traditional radar systems often struggle to detect newlinesmall targets under dynamic and cluttered sea background. newlineOn contrary, detecting such small targets under cluttered sea environment is newlineof paramount significance. Practically, sea clutter which is decisively dependent on newlinethe oceanic events, local weather condition such as wind speed, wind-direction, newlineheight of waves, and the grazing angle of radar. Therefore, it is important to develop newlinean efficient and robust model for the detection multiple moving targets under sea newlineclutter. newlineAmongst the major available radar signal processing approaches such as newlinesignal averaging, TFR, morphological, STFT and STAP based techniques, STFT and newlineSTAP has been found more robust. The ability to perform simultaneous time and newlinefrequency analysis for time-series assessment enables STFT to be used in small target newlinedetection in sea clutter; however, the inherent limitations such as improper newlineWindowing, window-size, number of samples, overlapping conditions affect overall newlineperformance.