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Single Station Passive Location And Tracking Technology

Posted on:2007-09-10Degree:MasterType:Thesis
Country:ChinaCandidate:L YuFull Text:PDF
GTID:2208360185455707Subject:Signal and Information Processing
Abstract/Summary:PDF Full Text Request
Passive localization and tracking technology plays an important role in the electronic warfare, because it works silently without any electromagnetic radiation. And since single observer passive localization and tracking (SOPLAT) technology avoid time synchronization and communication among observers, it becoming more and more popular in target localization field.Essentially, passive localization and tracking technology consists of localization and tracking measure methods and algorithms. They are the two key points of passive localization technology, which decide the precision and rapidity. Combining different localization measures and algorithms can bring in many kinds of localization methods. Thus, the dissertation does deeper researches on the two aspects.First of all, the passive localization technology is briefly analyzed in Chapter 1, including typical localization methods and filtering algorithms. In Chapter 2, the mathematical model of localization system is set up. Based on this model, the principle of many kinds of localization methods is discussed, and measure equation is set up. Then the performances and observability of different localization methods are analyzed.In Chapter 3, the estimation algorithms of localization are mainly discussed. EKF algorithm is analyzed. EKF algorithm is the most classical nonlinear method, successfully applying in many passive localization problems. The computer simulations are carried out, and the performance and restrict in practical application is analyzed.In order to avoid the weakness of EKF, SPKF algorithm is brought out. In Chapter 4, SPKF algorithm and its application in passive localization is studied deeply, especially, UKF is mainly studied. As one of the most popular nonlinear estimation algorithms, UKF is being studied and applied in passive localization by more and more researchers. Many simulations are carried out, and many valuable results are obtained. In addition, CDKF and Reduced Sigma Point algorithm also performs well in SOPLAT. The results of simulations indicate that they have similar performance of UKF.
Keywords/Search Tags:Single Observer Passive Localization, Bearing-Only Tracking, EKF, UKF, Particle Filter
PDF Full Text Request
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