摘要
现有认知雷达成像系统的资源调度策略只从距离向(或波形设计)或者方位向一个维度进行资源调度,没有充分分配和利用雷达系统资源,为此提出了一种针对步进频率逆合成孔径雷达成像系统的二维资源自适应调度算法,来进一步提高雷达系统的工作效率。该算法在对目标特征认知的基础上,根据压缩感知原理,计算对目标二维稀疏观测所需脉冲资源,依据二维资源调度模型,自适应分配二维脉冲资源,实现对多目标的交替稀疏观测成像。最后通过仿真验证了算法的可行性并与常规算法相比在资源饱和的情况下,可以执行更多的成像任务。
The resource scheduling strategy of the existing cognitive radar imaging system only performs resource scheduling from one dimension that distance(waveform design)or azimuth,which doesn’t adequately allocate and utilize radar system resources.Therefore,a two-dimensional resource adaptive scheduling algorithm is proposed for the stepped frequency inverse synthetic aperture radar imaging system to improve the efficiency of the radar system.Based on the recognition of target’s features and according to the principle of compressed sensing,the proposed algorithm calculates the pulse resources required for two-dimensional sparse imaging of targets.Then,according to the two-dimensional resource scheduling model,the two-dimensional pulse resources are adaptively allocated to realize the alternate observation of the target.Two-dimensional image of target is obtained by the sparse imaging algorithm.Finally,the feasibility of the algorithm is verified by simulation,and more imaging tasks can be performed compared with the traditional algorithm in the case of resource saturation.
作者
杜毅
廖可非
欧阳缮
陈怡君
DU Yi;LIAO Kefei;OUYANG Shan;CHEN Yijun(School of Information and Communication, Guilin University of Electronic Technology,Guilin 541004, China;State and Local Joint Engineering Research Center for Satellite Navigation andLocation Service,Guilin University of Electronic Technology,Guilin 541004, China;College ofInformation Engineering, Engineering University of CAPF, Xi’an 710086, China)
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2020年第2期339-345,共7页
Systems Engineering and Electronics
基金
国家自然科学基金(61631019,61701128,618714259)
广西自然科学基金(2017GXNSFBA198032)
桂林电子科技大学研究生优秀学位论文培育项目(17YJPYSS11)资助课题
关键词
步进频率
逆合成孔径雷达
压缩感知
资源调度
认知成像
step frequency
inverse synthetic aperture radar
compressive sensing
resource scheduling
cognitive imaging
