论文标题
关节检测的理论极限和雷达目标的估计
Theoretical Limits of Joint Detection and Estimation for Radar Target
论文作者
论文摘要
本文提出了基于雷达工作的共同信息的联合检测和估计方案（JDE）方案，其目标是在目标缺失和目标缺失之间选择真实的信息，并在目标存在时估算未知距离参数。受香农信息理论的思想的启发，JDE系统模型是在存在复杂的白色高斯噪声的情况下建立的。我们做出了几个主要贡献：（1）基于噪声，靶标散射和关节目标参数的先验统计特征得出等效的JDE通道和后验概率密度函数； （2）JDE系统的性能通过联合熵偏差和定义为接收信号和关节目标参数之间的相互信息的关节信息来衡量； （3）提出了采样后验概率和级联的JDEers，其性能是通过经验关节偏离经验信息来衡量的； （4）联合定理证明了联合信息是总体绩效的可用限制，即可用的联合信息，并且任何JDEER的经验联合信息都不大于联合信息； （5）证明了级联定理的经验检测信息和经验估计信息的总和可以近似联合信息，即提供级联JDEER的性能限制。仿真结果验证了关节和级联定理的正确性，并表明采样后概率JDEER的性能在渐近上是最佳的。此外，级联JDEER的性能可以近似JDE系统的系统性能。
This paper proposes a joint detection and estimation (JDE) scheme based on mutual information for the radar work, whose goal is to choose the true one between target existent and target absence, and to estimate the unknown distance parameter when the target is existent. Inspired by the thoughts of Shannon information theory, the JDE system model is established in the presence of complex white Gaussian noise. We make several main contributions: (1) the equivalent JDE channel and the posterior probability density function are derived based on the priori statistical characteristic of the noise, target scattering and joint target parameter; (2) the performance of the JDE system is measured by the joint entropy deviation and the joint information that is defined as the mutual information between received signal and the joint target parameter; (3) the sampling a posterior probability and cascaded JDEers are proposed, and their performance is measured by the empirical joint entropy deviation the empirical joint information; (4) the joint theorem is proved that the joint information is the available limit of the overall performance, that is, the joint information is available, and the empirical joint information of any JDEer is no greater than the joint information; (5) the cascaded theorem is proved that the sum of empirical detection information and empirical estimation information can approximate the joint information, i.e., the performance limit of cascaded JDEer is available. Simulation results verify the correctness of the joint and the cascaded theorems, and show that the performance of the sampling a posterior probability JDEer is asymptotically optimal. Moreover, the performance of cascaded JDEer can approximate the system performance of JDE system.
