Sparse frequency transmit waveform design with soft power constraint by using PSO algorithm

For many radar and communication applications, it is often difficult to find a clear wideband for operation. Sparse waveform design is to make use of a number of discontinuous clear narrow bands to achieve wideband performance while mitigating the interference. However, the broken spectrum may give rise to high range sidelobes, which can not be reduced by conventional methods. Because the soft power constraint method could make use of 2 degrees of freedom in waveform design, this paper presents a flexible optimization approach for sparse frequency waveform design based on this. By optimizing the objective function constructed based on the requirements of both the power spectral density and autocorrelation function (ACF), this approach could generate optimal waveforms in the sense of sparse frequency and sidelobe/grating lobe reduction in ACF. Meanwhile, the power variation of candidate signal could be well controlled within the radar power amplifier dynamic range, which would make it practical in the real radar system implementation. Particle Swarm Optimization (PSO) algorithm is taken as the optimization engine due to its global searching ability and the flexibility of implementation. A case study is presented to show the validity of this method.