摘要
随着机会照射源信号带宽越来越大,提升外辐射源雷达探测能力的同时导致杂波抑制的计算复杂度越来越大,杂波实时抑制已经成为外辐射源雷达面临的严峻挑战。针对该问题,设计了一种基于LDLT分解的扩展相消批处理算法(Extensive Cancellation Algorithm Batches,ECA-B)段间并行算法。基于图形处理器(Graphic Processing Unit,GPU)多线程并行处理技术并结合ECA-B各段相同子模块特性,通过分段并行处理提高ECA-B的时效性;针对传统ECA-B算法求逆过程中数据传输耗时问题,利用自相关矩阵共轭对称特性提出一种基于LDLT的并行迭代求逆方法,通过2个统一计算设备架构(Compute Unified Device Architecture,CUDA)核函数实现求逆处理,节省了矩阵求逆过程中数据传输的时间,进一步提升段间并行算法的实现效率。实验结果表明,与传统算法相比,提出的算法具有更高的时效性和有效性。
With the increasing bandwidth of the opportunity exposure source signal,improving the detection ability of passive radar also leads to an increasing computational complexity of clutter suppression.Therefore,real-time clutter suppression has become a serious challenge faced by passive radar.In response to this,an improved Extended Cancellation Algorithm Batches(ECA-B)is designed based on LDLT decomposition and inter-segment parallel algorithm.Firstly,based on the multithreading parallel processing technology of the Graphic Processing Unit(GPU)and the same submodule characteristics of each segment of the ECA-B,the efficiency of the ECA-B is improved through segmented parallel processing;Then,in response to the time-consuming problem of data transmission in the inversion process of the traditional ECA-B algorithm,a parallel iterative inversion method based on LDLT is proposed using the conjugate symmetry property of the autocorrelation matrix.The inversion process is achieved through two Compute Unified Device Architecture(CUDA)kernel functions,saving data transmission time in the matrix inversion process and further improving the implementation efficiency of inter-segment parallel algorithms.The experimental results show that the proposed algorithm has higher timeliness and effectiveness compared to traditional algorithms.
作者
贾东
温博
施健
罗扬静
王海涛
JIA Dong;WEN Bo;SHI Jian;LUO Yangjing;WANG Haitao(School of Information and Communication,Guilin University of Electronic Technology,Guilin 541002,China;The 54th Research Institute of CETC,Shijiazhuang 050081,China)
出处
《无线电工程》
2024年第1期150-156,共7页
Radio Engineering
基金
广西自然科学基金(2020GXNSFBA297078)
广西创新驱动发展专项(桂科AA21077008)
桂林电子科技大学研究生教育创新计划资助项目(2022YCXS053)。
