The high-resolution frequency estimators most commonly used, such as Least Square (LS) method based on AR model, MVSE, MUSIC and ESPRIT, determine estimates of the sinusoidal frequencies from the sample noise-corrupted data. In this paper, a new frequency estimation method named Pole-Placement Least Square (PPLS) is presented, which is a modified LS method with a certain number of model poles restricted to the unit circle. The statistical performance of PPLS is studied numerically, and compared with the Cramer-Rao bound as well as the statistical performance corresponding to the LS methods. PPLS is shown to have higher resolution than the conventional LS method. The relationship between poles location and its resolution is also discussed in detail.

A modified moving DFT algorithm and a new SMTD structure are proposed in this paper. The new SMTD structure adopts both batch-mode signal channel estimating and the modified moving DFT algorithm, which leads to dramatic decline of the computational load.

Based on filtering ground clutter power directly in the frequency domain, a new non-coefficient Adaptive MTI (AMTI) scheme is presented in this letter. The results of simulation example show that this scheme has smaller signal-to-noise ratio loss than the classical AMTI based on spectral estimation, as well as high improvement factor.