电子与信息学报
電子與信息學報
전자여신식학보
JOURNAL OF ELECTRONICS & INFORMATION TECHNOLOGY
2013年
1期
68-73
,共6页
李望西*%黄长强%王勇%韩统%唐传林%蚩军祥
李望西*%黃長彊%王勇%韓統%唐傳林%蚩軍祥
리망서*%황장강%왕용%한통%당전림%치군상
机载无源定位%空频域信息%相位差变化率%简化球形分布平方根UKF
機載無源定位%空頻域信息%相位差變化率%簡化毬形分佈平方根UKF
궤재무원정위%공빈역신식%상위차변화솔%간화구형분포평방근UKF
Airborne passive location%Spatial-frequency domain information%Phase difference rate of change%Simplex spherical distribution square root Unscented Kalman Filter (UKF)
为解决基于空频域信息的机载无源定位中高精度角速度参数难以获取的问题,论文利用相位差变化率对角速度的放大作用,通过2维相位干涉仪布局建立了一种新的无源定位观测模型,实现了对空中运动目标的定位.针对UKF(Unscented Kalman Filter)滤波中误差协方差矩阵负定导致滤波不稳定的问题,引入平方根UKF滤波算法并进行改进,采用简化球形分布的SSUT(Simplex Spherical distribution Unscented Transform)变换进行Sigma点采样,通过减少采样点个数减小了滤波的计算量.仿真表明:在较低的参数测量精度条件下,新观测模型位置和速度跟踪误差降低,采用改进的平方根UKF算法能够在保证稳定跟踪的同时,提高算法效率.
為解決基于空頻域信息的機載無源定位中高精度角速度參數難以穫取的問題,論文利用相位差變化率對角速度的放大作用,通過2維相位榦涉儀佈跼建立瞭一種新的無源定位觀測模型,實現瞭對空中運動目標的定位.針對UKF(Unscented Kalman Filter)濾波中誤差協方差矩陣負定導緻濾波不穩定的問題,引入平方根UKF濾波算法併進行改進,採用簡化毬形分佈的SSUT(Simplex Spherical distribution Unscented Transform)變換進行Sigma點採樣,通過減少採樣點箇數減小瞭濾波的計算量.倣真錶明:在較低的參數測量精度條件下,新觀測模型位置和速度跟蹤誤差降低,採用改進的平方根UKF算法能夠在保證穩定跟蹤的同時,提高算法效率.
위해결기우공빈역신식적궤재무원정위중고정도각속도삼수난이획취적문제,논문이용상위차변화솔대각속도적방대작용,통과2유상위간섭의포국건립료일충신적무원정위관측모형,실현료대공중운동목표적정위.침대UKF(Unscented Kalman Filter)려파중오차협방차구진부정도치려파불은정적문제,인입평방근UKF려파산법병진행개진,채용간화구형분포적SSUT(Simplex Spherical distribution Unscented Transform)변환진행Sigma점채양,통과감소채양점개수감소료려파적계산량.방진표명:재교저적삼수측량정도조건하,신관측모형위치화속도근종오차강저,채용개진적평방근UKF산법능구재보증은정근종적동시,제고산법효솔.
In order to solve the problem that it is difficult to acquire high precision angular velocity parameter in airborne passive location based on spatial-frequency domain information, this paper utilizes phase difference rate-of-change’s augmentation to angular velocity, and constructs a new passive location measure model by two dimensions interferometer layout. The passive location of air target is realized. For the negative error covariance matrix possibly induces instability in the Unscented Kalman Filter (UKF), the square root UKF is introduced and improved. The Simplex Spherical distribution Unscented Transform (SSUT) is used to sigma sampling. The calculated amount of filtering is reduced by cutting down the number of sampling point. The simulation results show that the position and velocity tracking error of the new measure model decrease under the lower condition of parameters measurement. When the stable tracking effect can be reached, the algorithm efficiency can be enhanced by adopting improved square root UKF.