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Multi-Static-Radar (MSR) systems are emerging technology due to exploitation of spatial diversity nature, offering improved Performance for various configuration of deployment of vis a vis mono-static radar. The deployment challenges becomes more difficult when all radar are considered as airborne radar and creates scenario of Multi-Dynamic radar(MDR). The radar signal characteristics for MDR scenario dynamically changing based on geometrical configuration. The Transmit and Receive pairs in MDR case is considered on moving airborne-platform such that Airborne radar with multiple receiver(Rx) mounted on different Unmanned Aerial Vehicles (UAVs), such configuration considered as Multi-dynamic radar for airborne surveillance systems. Space Time Adaptive Processing(STAP) is considered as multi-dimensional adaptive-filtering algorithms that simultaneously combine and process the signals received from the array elements (spatial domain) and multiple pulses (Temporal domain) of coherent radar waveform to suppress the interference. STAP for multi-dynamic radar scenario improve detection of stealth or low rcs targets obscured by mainlobe clutter and jamming environments as detection performance depends on Receivers coordinated network. A typical interference scenario involves the detection of a low rcs targets(SNR) in the presence of a large interfering signal, it is desirable to attenuate the interfering signal while preserving the integrity of low rcs target and an appropriate dynamic range. This paper discusses the reduced rank algorithm to reduce the rank of sample covariance matrix in sample starved homogeneous environment. The two solutions namely, multi-stage Weiner filter and Principal Component (PC) have been shown. Keywords: Bi-static Radar, Multi-dynamic Radar, Multi-static Radar, STAP, clutter, jammer, MWF, PC. |
