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An unsatisfactory property of particle filters is that they
may become inefficient when the observation noise is low.
In this paper we consider a simple-to-implement particle filter,
called ‘LIS-based particle filter’, whose aim is to overcome
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基于粒子滤波实现的纯方位目标跟踪，最后证明该算法收敛-Particle filter based on the realization of the bearings-only target tracking, the final proof of the convergence of the algorithm
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纯方位目标跟踪中的观测器机动优化研究和如何实现的方法(2)-Bearings-only Target Tracking mobile optimization of observer and how to implement the method (2)
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BOT模型的一种跟踪方法，使用粒子滤波实现-BOT model of a tracking method, using the particle filter implementation
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本文分别就纯方位角跟踪中的机动目标跟踪、有信号传输时延时的跟踪及一类特定的多目标跟踪问题进行了较为系统和深入的研究。首先，针对非机动目标提出一种智能距离参数化无味滤波方法，与传统方法相比，改进了跟踪初始性能、滤波精度以及优化了系统资源。其次，针对机动目标纯方位角跟踪提出一种将交互多模型和核粒子滤波结合的方法，在维持跟踪精度的前提下，大幅减少了所需粒子数，改善了系统实时性。-This paper bearings-only tracking of maneuvering target tracki
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基于粒子滤波实现的纯方位目标跟踪踪，最后证明该算法收敛可直接使用。
-Tracking based on particle filter implementation of the bearings-only target tracking, and finally prove the convergence can be used directly.
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基于多站纯方位被动定位算法仿真程序（分为CA模型和CA模型，经matlab command window运行通过）-Bearings based on multi-station passive location algorithm simulation program (divided into the CA model and CA model, the matlab command window run through)
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扩展Kalman滤波在纯方位目标跟踪中的应用实例-Application of Extended Kalman Filter in Bearings- only Target Tracking
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可以解决纯方位跟踪系统的CKF滤波，针对单个两个平台之间。(It can solve the CKF filtering of bearings only tracking system for single two platforms.)
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