Extended target detection performance can be enhanced by using phase-modulated waveform designs in band-limited radar systems. Unlike waveforms designed for the total energy constraint, phase-modulated waveforms can fully exploit the transmit power in the pulse duration, which is more suitable for practical radar systems. An alternating iterative algorithm was developed to optimize the phase-modulated baseband waveform by maximizing the signal-to-noise ratio (SNR) at the receiver filter output. The output SNR increases continuously with the number of iterations and the algorithm is guaranteed to converge. Simulations validate the effectiveness of this approach. The waveforms designed by this method outperform other commonly used waveforms for extended target detection.

It is an important issue to study sea clutter suppression because it could interfere with the detection of targets above the sea surface severely. Spatial spectrum analyses show that the majority of sea clutter has low-frequency characteristics, compared to the high-frequency characteristics of the targets. This paper proposes a frequency-based spatial tracking filter to suppress sea clutter to facilitate targets identification. Experimental results show that the signal-to-clutter ratio can increase by more than 10 dB after filtering and the algorithm is feasible for practical use. In addition, the filtering equation can be optimized to maximize the signal-to-clutter ratio improvement. The equation parameters can also be adjusted to give a proper cut-off frequency for different targets and clutter.

Navigation and surveillance applications require tracking constant input/bias targets. When the target’s trajectory follows a constant input/bias constraint, model mismatching caused by conventional tracking algorithms can be handled by a delayed update filter (DUF). The statistical convergence and stability properties of the delayed update filter were studied to insure the rationality of its steady-state analysis. A steady-state filter gain was then designed for a constant-gain DUF to reduce the computations without much performance loss. Simulations demonstrate the potential of the constant-gain DUF, and the CGDUF is nearly 60% faster than the DUF without much loss in steady-state tracking accuracy.