Multiframe track-before-detect method based on velocity filtering in mixed coordinates

In this paper,a velocity filtering based track-before-detect algorithm in mixed coordinates is presented to address the problem of integration loss caused by inaccurate motion model in polar coordinate sensors.Since the motion of a con-stant velocity(CV)target is better modeled in Cartesian coordi-nates,the search of measurements for integration in polar sensor coordinates is carried out according to the CV model in Cartesian coordinates instead of an approximate model in polar sensor coordinates.The position of each cell is converted into Cartesian coordinates and predicted according to an assumed velocity.Then,the predicted Cartesian position is converted back to polar sensor coordinates for multiframe accumulation.The use of the correct model improves integration effectiveness and consequently improves algorithm performance.To handle the weak target with unknown velocity,a velocity filter bank in mixed coordinates is presented.The influence of velocity mis-match on the performance of filter bank is analyzed,and an effi-cient strategy for filter bank design is proposed.Numerical re-sults are presented to demonstrate the effectiveness of the pro-posed algorithm.

Nonlinear Reduced DNN Models for State Estimation

We propose in this paper a data driven state estimation scheme for generating nonlinear reduced models for parametric families of PDEs, directly providingdata-to-state maps, represented in terms of Deep Neural Networks. A major constituentis a sensor-induced decomposition of a model-compliant Hilbert space warranting approximation in problem relevant metrics. It plays a similar role as in a ParametricBackground Data Weak framework for state estimators based on Reduced Basis concepts. Extensive numerical tests shed light on several optimization strategies that areto improve robustness and performance of such estimators.

Three-dimensional analysis of relationship between relative orientation and motion modes

Target motion modes have a close relationship with the relative orientation of missile-totarget in three-dimensional highly maneuvering target interception. From the perspective of relationship between the sensor coordinate system and the target body coordinate system, a basic model of sensor is stated and the definition of relative angular velocity between the two coordinate systems is introduced firstly. Then, the three-dimensional analytic expressions of relative angular velocity for different motion modes are derived and simplified by analyzing the influences of target centroid motion, rotation around centroid and relative motion. Finally, the relationships of the relative angular velocity directions and values with motion modes are discussed. Simulation results validate the rationality of the theoretical analysis. It is demonstrated that there are significant differences of the relative orientation in different motion modes which include luxuriant information about motion modes. The conclusions are significant for the research of motion mode identification,maneuver detection, maneuvering target tracking and interception using target signatures.