This paper addresses the single target tracking problem of noncooperative bistatic radar using the phased array radar (PAR) as the illuminator. In addition to missed detections, false alarms, and the nonlinear measurement model, the intermittent and unknown signal illumination from the noncooperative PAR is the major challenge. This paper establishes a binary random variable to represent the intermittent property of signal illumination, and uses the Bernoulli/Markov process to describe its prior probability distribution. In the Bayesian framework, this paper constructs the joint probability density function (PDF) incorporating the kinematic state of the target and the unknown intermittent property of signal illumination, and proposes the soft Bayesian filter (SBF) and the hard Bayesian filter (HBF). Furthermore, this paper uses two groups of particles to describe the joint PDF, and proposes the particle filtering implementation of the SBF and the HBF. In addition, this paper proposes the intermittent Bayesian filter (IBF) and its particle filtering implementation for single target tracking with cooperative PAR illuminator, which is adopted as the baseline to evaluate the performance of the SBF and the HBF. Computer simulations demonstrate the effectiveness of proposed methods, and evaluate their performance with respect to different signal illumination modes and measurement noises.

本文以相控阵雷达（PAR）为照明源，解决了非合作型双基地雷达的单目标跟踪问题。除了错过的检测，错误警报和非线性测量模型之外，来自非合作PAR的间歇性和未知信号照明也是主要挑战。本文建立了一个二进制随机变量来表示信号照明的间歇性，并使用伯努利/马尔可夫过程描述其先验概率分布。在贝叶斯框架下，结合目标的运动状态和信号照明的未知间歇特性，构造了联合概率密度函数（PDF），并提出了软贝叶斯滤波器（SBF）和硬贝叶斯滤波器（HBF）。此外，本文使用两组粒子来描述联合PDF，并提出了SBF和HBF的粒子滤波实现。此外，本文提出了间歇性贝叶斯滤波器（IBF）及其粒子滤波的协同PAR照明器用于单目标跟踪的实现，以此为基础来评估SBF和HBF的性能。计算机仿真证明了所提出方法的有效性，并评估了它们在不同信号照明模式和测量噪声方面的性能。提出了间歇性贝叶斯滤波器（IBF）及其粒子滤波的协同PAR照明器对单目标跟踪的实现，以此为基准来评估SBF和HBF的性能。计算机仿真证明了所提出方法的有效性，并评估了它们在不同信号照明模式和测量噪声方面的性能。提出了间歇性贝叶斯滤波器（IBF）及其粒子滤波的协同PAR照明器对单目标跟踪的实现，以此为基准来评估SBF和HBF的性能。计算机仿真证明了所提出方法的有效性，并评估了它们在不同信号照明模式和测量噪声方面的性能。