Abstract
In this paper, an adaptive algorithm is proposed to develop an orthogonally optimized waveforms with good correlation properties that are suitable for the detection of target in the presence of strong clutter. The joint optimization both at the transmitter and receiver is adapted based on the secondary data and clutter to maximize signal to interference noise ratio (SINR) with target and clutter knowledge. The result shows good correlation properties and better SINR and signal to clutter ratio (SCR) compared to the existing iterative algorithm. The proposed algorithm also shows improved detection even for lower SCR when implemented with GLRT.
Highlights
Multiple input and multiple output systems (MIMO) radiate multiple probing signals through it their transmit antennas and receive multiple coded waveforms from multiple locations
Deng et al (2004) has proposed simulated annealing (SA) algorithm to optimize the frequency sequences for the development of the orthogonal discrete frequency coding waveforms frequency hopping (DFCW_FF) for netted radar systems
The autocorrelation sidelobe peak (ASP) and crosscorrelation peak (CP) for the corresponding waveforms are shown in Table 3 in presence of compound Gaussian clutter and extended target
Summary
Multiple input and multiple output systems (MIMO) radiate multiple probing signals through it their transmit antennas and receive multiple coded waveforms from multiple locations. The two-stage waveform optimization (Nijsure et al 2013) algorithm maximizes signal-to-clutter-plus-noise ratio (SCNR) for adaptive distributed MIMO radar. The optimization of both waveforms and the receiving filters by iterative algorithm (Chen and al 2009) maximizes signal-to-interference noise ratio (SINR).
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