摘要本文梳理了粒子滤波理论基本内容, 发展脉络和最新研究进展, 特别是对其在多目标跟踪
应用中的一系列难点问题与主流解决思路进行了详细分析和报道. 常规粒子滤波研究重点主要 …

The standard way of applying particle filtering to stochastic hybrid systems is to make use of
hybrid particles, where each particle consists of two components, one assuming Euclidean …

Tracking multiple maneuvering targets hidden in the Doppler blind zone (DBZ) is a
challenging problem. To overcome the complicated problem, we proposed a tracker based …

In this paper, we propose a new approach to state estimation of multiple state-space models.
Unlike the traditional methods (including the interacting multiple-model algorithm) that …

Motivated by the complementary features of the IIR-type filter and the FIR-type filter, this
paper proposes a robust IIR/FIR fusion filter and an INS/GPS integrated system designed …

In practice, the designed nominal model set for a jump (Markov) linear system might be
uncertain: 1) Every candidate model might be inexact due to, eg, mismatched modeling …

The interacting multiple model (IMM) estimator outperforms fixed model filters, eg the
Kalman filter, in scenarios where the targets have periods of disparate behavior. Key to the …

High-precision navigation solutions are essential requirements for various industries,
especially the autonomous robotics industry. Inertial navigation systems (INS) are the prime …

Numerous satellites with electric propulsion perform long duration maneuvers during their
orbit acquisition phase. This poses a challenge to space object cataloging activities if no …

The problem of state space estimation of linear systems in an unknown non-Gaussian noise
field is considered. A finite Gaussian mixture model (GMM) is used to model the non …