Augmentation of minimum redundant radar observations for improved estimation performance

In this paper it is proposed that spectrally sparse radar signals are providing significant advantages for the range estimation performance in terms of multiple target resolution capability as well as distance accuracy. It is shown that using multicarrier signals with a structured arrangement of frequency steps on a uniform spectral grid, minimizing equal differential frequency lags, yields the same amount of information as obtained with a common radar signal spanning the whole spectrum. The minimum redundant waveforms do not only allow a considerable reduction of the utilized effective bandwidth without a loss in ranging performance, but also provide detection and parameter estimation capability for more targets compared to traditional radar signals consisting of the same number of equally spaced frequency steps. In order to account for the missing elements in the covariance matrix, a data processing method is described that can handle the sparsity of the measurements and obtain the same amount of information as would be available when using signals occupying the complete spectrum. The effectiveness of the augmentation method, as well as the improvements in the distance estimation are demonstrated based on Monte Carlo simulations.