Performance Analysis for Applying Recursive Least-Square Processing to Passive-Position Location

最小平方遞迴處理應用於被動式目標定位系統的性能分析

陳雍宗(Joy Iong-Zong Chen)

《大葉學報》 11卷1期 (2002/06) Pp. 71-79

https://doi.org/10.7119/JDYU.200206.0071

摘要

本論文中，研究者提出應用最小平方遞迴處理（recursive least squares processing）方式於被動式定位系統，以達到節省處理時間之目的。同時，我們分析非線性最小平方批次處理與遞迴處理、擴展性卡爾曼濾波器及疊代擴展性卡爾曼濾波器等四種濾波器性能，並發展出一套混合定位法則（hybrid position algorithm），用以分析被動式目標定位系統對飛行路徑的不同起始點之定位誤差距離。經由最後效能數值分析的結果發現，利用此一混合定位法則於定位系統確實擁有較精確地定位效能。

關鍵字

最小平方批次處理 ； 最小平方遞迴處理 ； 擴展性卡爾曼濾波器

並列摘要

In this study, the recursive least-square processing algorithm, which can reduce processing time, is applied to passive-position location. The performance of four different estimation schemes are also analyzed and evaluated, namely, nonlinear least-square batch processing, nonlinear least-square recursive processing, extended Kalman filter, and iterated extended Kalman filter. A hybrid position algorithm for passive-position location is thereby developed. Numerical results indicate that the new algorithm indeed increases the accuracy of local positioning. Locating error distance in passive target positions for various initial positions of aircraft is also analyzed.

並列關鍵字

least-square batch processing ； recursive least-square processing ； extended Kalman filter