摘要
针对基于多输入多输出(MIMO)正交频分复用(OFDM)雷达的空时自适应处理(STAP)方法的检测性能受未确知环境先验信息影响较大的问题,提出一种提升空时自适应检测性能的MIMO雷达稳健波形设计方法。首先构建杂波协方差矩阵估计误差模型,然后在此误差模型以及波形恒模特性约束下,基于最大化最差情况下的输出信干噪比准则,建立改善STAP检测概率稳健性的波形优化模型。为求解所得非线性波形优化模型,提出了基于对角加载的迭代方法,该迭代方法中每步均可转化为半定规划问题,因而可以获得高效求解。仿真结果表明,所提方法能够改善最差情况下的STAP检测概率,与非稳健方法以及不相关波形相比,可提高最差情况下MIMOOFDM-STAP方法的输出信干噪比2~4dB。
A robust waveform design method of multi-input multi-output （MIMO）radars for improving the detection performance of space-time adaptive processing （STAP）is presented to focus the issue that the detection performance of the MIMO-OFDM radar based STAP method is heavily affected by the unascertained environmental prior knowledge. An estimation error model for clutter covariance matrix is firstly constructed. Then, with the constraints of this error model and waveform constant modulus, the waveform optimization issue to improve the robustness of the detection probability of STAP can be formulated, which is based on the criterion of maximizing the worst-case output signal-to-interference plus noise ratio （SINR）. To solve the resultant nonlinear waveform optimization problem, an iterative approach based on diagonal loading is developed. Each step in the proposed iterative method can be recast as a semidefinite programming, and can be solved in an efficient way. Simulation results show that the proposed approach can improve the detection probability of STAP in the worst case, and in comparisons with the uncorrelated waveforms and the non-robust algorithm, the proposed method can improve the worst-case output of MIMO-OFDM-STAP SINR by 2 - 4 dB.
作者
刘玉春
王洪雁
LIU Yuchun1,WANG Hongyan2.(1. School of Mechanical and Electrical Engineering,Zhoukou Normal University, Zhoukou,Henan 466001, China;2. College of Information Engineering,Dalian University, Dalian,Liaoning 116622, Chin)
出处
《西安交通大学学报》
EI
CAS
CSCD
北大核心
2018年第8期124-131,共8页
Journal of Xi'an Jiaotong University
基金
国家自然科学基金资助项目(61401526
61301258)
国家博士后基金资助项目(2016M590218)
关键词
雷达
正交频分复用
多输入多输出
空时自适应处理
稳健设计
半定规划
radar
orthogonal frequency division multiplexing
multi-input multi-output
space-time adaptive processing
robust design
semidefinite programming
