It is a tough problem to jointly detect and track a weak target, and it becomes even more challenging when the target is maneuvering. The above problem is formulated by using the Bayesian theory and a multiple model(M...It is a tough problem to jointly detect and track a weak target, and it becomes even more challenging when the target is maneuvering. The above problem is formulated by using the Bayesian theory and a multiple model(MM) based filter is proposed. The filter presented uses the MM method to accommodate the multiple motions that a maneuvering target may travel under by adding a random variable representing the motion model to the target state. To strengthen the efficiency performance of the filter,the target existence variable is separated from the target state and the existence probability is calculated in a more efficient way. To examine the performance of the MM based approach, a typical track-before-detect(TBD) scenario with a maneuvering target is used for simulations. The simulation results indicate that the MM based filter proposed has a good performance in joint detecting and tracking of a weak and maneuvering target, and it is more efficient than the general MM method.展开更多
This paper presents the derivation of Gauss-Newton filter in linear cases and an analysis of its properties. Based on the minimum variance theorem, the Gauss-Newton filter is constructed and derived, including its sta...This paper presents the derivation of Gauss-Newton filter in linear cases and an analysis of its properties. Based on the minimum variance theorem, the Gauss-Newton filter is constructed and derived, including its state transition equation, observation equation and filtering process. Then, the delicate relationship between the Gauss-Aitken filter and the Kalman filter is discussed and it is verified that without process noise the two filters are equivalent. Finally, some simulations are conducted. The result shows that the Gauss-Aitken filter is superior to the Kalman filter in some aspects.展开更多
Based on principle of power synthesis of sparse array, mathematical model of spatial power combining is established. Relation between cross angle of beams and synthesis efficiency on aimed point from two antenna nodes...Based on principle of power synthesis of sparse array, mathematical model of spatial power combining is established. Relation between cross angle of beams and synthesis efficiency on aimed point from two antenna nodes is derived. Furthermore, the setting principle of sampling interval is analyzed for simulation experiment. Energy distributions of the useful points under different cross angles were simulated. Simulation shows that if distance between the antenna nodes and aimed point are equal, and frequency, polarization and an- tenna type are the same, synthesis efficiency relies on the cross angles of beams, shape and density on the useful points accumulation area also rely on the cross angles of beams.展开更多
基金supported by the Natural Science Foundation of Anhui Province(1708085QF149)。
文摘It is a tough problem to jointly detect and track a weak target, and it becomes even more challenging when the target is maneuvering. The above problem is formulated by using the Bayesian theory and a multiple model(MM) based filter is proposed. The filter presented uses the MM method to accommodate the multiple motions that a maneuvering target may travel under by adding a random variable representing the motion model to the target state. To strengthen the efficiency performance of the filter,the target existence variable is separated from the target state and the existence probability is calculated in a more efficient way. To examine the performance of the MM based approach, a typical track-before-detect(TBD) scenario with a maneuvering target is used for simulations. The simulation results indicate that the MM based filter proposed has a good performance in joint detecting and tracking of a weak and maneuvering target, and it is more efficient than the general MM method.
文摘This paper presents the derivation of Gauss-Newton filter in linear cases and an analysis of its properties. Based on the minimum variance theorem, the Gauss-Newton filter is constructed and derived, including its state transition equation, observation equation and filtering process. Then, the delicate relationship between the Gauss-Aitken filter and the Kalman filter is discussed and it is verified that without process noise the two filters are equivalent. Finally, some simulations are conducted. The result shows that the Gauss-Aitken filter is superior to the Kalman filter in some aspects.
文摘Based on principle of power synthesis of sparse array, mathematical model of spatial power combining is established. Relation between cross angle of beams and synthesis efficiency on aimed point from two antenna nodes is derived. Furthermore, the setting principle of sampling interval is analyzed for simulation experiment. Energy distributions of the useful points under different cross angles were simulated. Simulation shows that if distance between the antenna nodes and aimed point are equal, and frequency, polarization and an- tenna type are the same, synthesis efficiency relies on the cross angles of beams, shape and density on the useful points accumulation area also rely on the cross angles of beams.
