To keep the system complexity at a reasonable level and conform to the propagation demands, MIMO arrays are usually sparse in through-the-wall applications, which results in corrupted and gapped data. The corresponding imaging results are seriously affected by the high-level sidelobes. To solve this problem, a new imaging model for ultra-wideband (UWB) MIMO arrays is constructed via spatial spectrum theory in this paper. Based on the model, the characteristics of the spatial spectrum for the MIMO array and its effects on imaging are discussed. To improve the imaging quality, a through-the-wall imaging enhancement method is proposed via spatial spectrum estimation. Synthetic and experimental results show that, unlike the conventional amplitude weighting methods and nonlinear techniques, the proposed method can efficiently suppress sidelobes in the imagery, especially for the sparse MIMO array, and consequently improve the target image quality without degrading the mainlobe resolution. The proposed method has been successfully used in our real through-the-wall radar system
