系统工程与电子技术
繫統工程與電子技術
계통공정여전자기술
SYSTEMS ENGINEERING AND ELECTRONICS
2015年
1期
42-47
,共6页
张向阳%廖桂生%许京伟%曾操
張嚮暘%廖桂生%許京偉%曾操
장향양%료계생%허경위%증조
多输入多输出雷达%概率约束%波形设计%稳健算法%最优化
多輸入多輸齣雷達%概率約束%波形設計%穩健算法%最優化
다수입다수출뢰체%개솔약속%파형설계%은건산법%최우화
multi-input multi-output (MIMO)radar%probabilistic constraint%waveform design%robust arithmetic%optimization
传统多输入多输出(multi-input multi-output,MIMO)雷达发射波形设计方法对传播矩阵误差敏感,导致难以得到最优的匹配波形,进而造成系统检测性能严重下降。针对此问题,提出一种基于概率约束的 MIMO雷达稳健发射波形设计方法。该方法考虑最差情况的发生为小概率事件,基于输出信噪比(signal noise ratio, SNR)低于可接受水平的概率小于中断概率的约束条件,通过最大化输出信噪比设计最优波形。利用传播矩阵误差的概率分布特性,将概率约束转化为凸约束,从而将统计优化问题转化为确定性优化问题。该方法在传播矩阵存在误差情况下以高概率实现系统性能最优化。仿真结果表明所提方法能够提高输出 SNR,具有较好的检测性能。
傳統多輸入多輸齣(multi-input multi-output,MIMO)雷達髮射波形設計方法對傳播矩陣誤差敏感,導緻難以得到最優的匹配波形,進而造成繫統檢測性能嚴重下降。針對此問題,提齣一種基于概率約束的 MIMO雷達穩健髮射波形設計方法。該方法攷慮最差情況的髮生為小概率事件,基于輸齣信譟比(signal noise ratio, SNR)低于可接受水平的概率小于中斷概率的約束條件,通過最大化輸齣信譟比設計最優波形。利用傳播矩陣誤差的概率分佈特性,將概率約束轉化為凸約束,從而將統計優化問題轉化為確定性優化問題。該方法在傳播矩陣存在誤差情況下以高概率實現繫統性能最優化。倣真結果錶明所提方法能夠提高輸齣 SNR,具有較好的檢測性能。
전통다수입다수출(multi-input multi-output,MIMO)뢰체발사파형설계방법대전파구진오차민감,도치난이득도최우적필배파형,진이조성계통검측성능엄중하강。침대차문제,제출일충기우개솔약속적 MIMO뢰체은건발사파형설계방법。해방법고필최차정황적발생위소개솔사건,기우수출신조비(signal noise ratio, SNR)저우가접수수평적개솔소우중단개솔적약속조건,통과최대화수출신조비설계최우파형。이용전파구진오차적개솔분포특성,장개솔약속전화위철약속,종이장통계우화문제전화위학정성우화문제。해방법재전파구진존재오차정황하이고개솔실현계통성능최우화。방진결과표명소제방법능구제고수출 SNR,구유교호적검측성능。
Conventional waveform design methods for multiple-input multiple-output (MIMO)radars are sensitive to transport matrix errors,so the optimal matched-waveform is hard to achieve,and the detection performance de-grades dramatically.To mitigate this problem,a novel robust waveform design method is introduced for MIMO radars based on probabilistic constraint.In this method,the probability of the worst case is considered very small.Therefore, the probability of the output signal noise ratio (SNR)less than the acceptable level is constrained no more than the out-age probability,and the optimal waveforms are designed to maximize the output SNR.Using the characters of statisti-cal distribution of transport matrix errors,the probabilistic constraint is transformed to a deterministic convex con-straint.So the statistical optimization problem is converted to a convex optimization problem.This method maximizes the performance with high probability under transport matrix errors.The simulation results show that the method in-creases the output SNR and detection performance.