A Novel Waveform Optimization Framework It is well known that the nonlinear frequency modulation (NLFM) waveform with the advantage that it can shape the power spectral density (PSD) to provide a radar matched filter output with lower sidelobe without the loss of signaltonoise ratio (SNR) when compared with the linear frequency modulation (LFM) waveform. But NLFM waveform would also broaden the main lobe and reduce the range resolution. In this paper, we report a novel waveform optimization framework. Through this framework, an advanced nonlinear frequency modulation (NLFM) waveform with lower sidelobes and a smaller main lobe is constructed. In addition, we apply it in a real synthetic aperture radar (SAR) system with a bandwidth of 100 MHz at 9.6 GHz carrier frequency and the imaging results validate the proposed NLFM waveform.

Constrained Transmit Beampattern Design Using a Correlated LFMPC Waveform Set in MIMO Radar This paper considers the design of a desired transmit beampattern under the good ambiguity function constraint using a correlated linear frequency modulationphase coded (LFMPC) waveform set in multipleinputmultipleoutput (MIMO) radar. Different from most existing beampattern design approaches, we propose using the LFMPC waveform set to conquer the challenging problem of synthesizing waveforms with constantenvelope and easygeneration properties, and, meanwhile, solve the hard constraint of a good ambiguity behaviour. First, the ambiguity function of the LFMPC waveform set is derived, and the superiority of LFMPC waveforms over LFM and PC waveforms is verified. The temporal and spatial characteristic analysis of the LFMPC waveform set demonstrates that both the transmit beampattern and sidelobe level are mainly affected by the frequency intervals, bandwidths, and phasecoded sequences of the LFMPC waveform set. Finally, the constrained beampattern design problem is formulated by optimizing these parameters for desired beampatterns and low sidelobes at different doppler frequencies, which is a biobjective optimization problem. To solve this, we propose a joint optimization strategy followed by a mandatory optimization, where the sequence quadratic programming (SQP) algorithm and adaptive clonal selection (ACS) algorithm are exploited iteratively. The simulation results demonstrate the efficiency of our proposed method.