With the development of compressive sensing theory ,the space-time adaptive processing (STAP ) technology based on sparsity of space-time power spectrum (STPS) receives a growing interest .This paper firstly reviews the traditional STAP algorithms and shows analysis of sparsity of STPS from three different points of view and potential advantages of STAP technology based on sparsity of STPS .Then ,the current developed STAP algorithms based on sparsity of STPS are categorized into three class-es ,such as STAP based on prior knowledge of array manifold ,STAP based on sparse recovery of STPS and STAP based on both prior knowledge of array manifold and sparse recovery of STPS .It also performs an overview of those algorithms .Finally ,based on the progress of the existing research ,some key issues to enhance the performance of clutter suppression and moving target detection are introduced ,which include intrinsic mechanism analysis of sparsity ,space-time steering dictionary design ,easy parameters setting , fast and low complexity algorithms design ,robust algorithm design ,STAP algorithms based on sparse recovery of STPS design by exploiting different types of prior knowledge ,and constant false alarm rate detector design of STAP based on sparsity of STPS and validation using measurement data .%随着压缩感知理论的兴起和发展，基于空时功率谱稀疏性的空时自适应处理（STAP ）技术受到越来越广泛的关注。本文首先简单回顾了空时自适应处理技术的传统方法，接着从三个不同角度分析了空时功率谱的稀疏性并探讨了基于空时功率谱稀疏性的STAP技术的潜在优势，然后总结了基于空时功率谱稀疏性STAP基本原理和三种实现方式，根据稀疏支撑集先验信息知晓情况对现有基于空时功率谱稀疏性的STAP方法进行了分类，包括：基于阵列流形知识的STAP技术、基于空时功率谱稀疏恢复的STAP技术以及基于阵列流形知识和空时功率谱稀疏恢复的STAP技术，并对其研究现状进行了综述。最后在已有研究的基础上，着眼于提高杂波抑制和运动目标检测能力的发展需要，提出了未来该技术需要重点解决和关注的若干问题，包括稀疏性的本质机理分析、空时导向字典的设计、参数设置简单，快速和低复杂度算法设计、对模型误差稳健的算法设计、多种先验知识融合的基于空时功率谱稀疏性的STAP算法设计、基于空时功率谱稀疏性STAP方法的恒虚警检测器设计以及实测数据验证等方面。
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