Joint mode identification and localisation improvement of over‐the‐horizon radar with forward‐based receivers

Abstract

Target tracking of over-the-horizon radar (OTHR) suffers from the effect of multi-path propagation. To date, all corresponding tracking methods depend on the precondition that the ionospheric heights should be available via the ionosondes. However, the ionosondes cannot be arbitrary deployed, for example, in sea area or hostile zone. This study presents the problem of sensor fusion of OTHR and a set of forward-based receivers (FBRs) for online mode identification of OTHR echoes, estimation of virtual ionospheric heights and localisation improvement. This fusion problem faces two challenges. The first is 'multi-path', as a kind of uncertainty existing in both the forward propagation of FBRs and the forward/backward propagation of OTHR. The other is 'coupling', representing the complexity that the mode/parameter identification and estimation couple each other. Here the joint optimisation scheme of identification and estimation is proposed mainly including four sub-processes: coordinate mapping with target height, joint identification and estimation of FBRs, mode identification of OTHR and localisation improvement. The simulation shows that propagation/clutter modes can be identified effectively and ionospheric heights are estimated without the help of ionosondes. Meanwhile, target state including the target height is estimated and the localisation accuracy is further improved due to sensor fusion.

Constrained State Estimation for Individual Localization in Wireless Body Sensor Networks

“…In order to prove that the proposed constrained state estimation can also be applied in non-Baysian methods, individual localization based on nonlinear iterative least square (NILS) [ 22 ] is simulated here. It can be seen from Figures 13 and 14 , that the constrained NILS provides much more accurate estimates than the unconstrained NILS, which verifies the effectiveness of the proposed method.…”

“…In this paper, our contribution is that we propose the constrained IMM-EKF algorithm for UWB based individual localization, exploit second-order nonlinear state constraints providing better approximation for higher order nonlinearities and demonstrate the effectiveness of the new method on an individual localization example, compared with the unstrained IMM-EKF. Note that, even the proposed constrained state estimation method is intended for Bayesian filtering algorithm, it can also be applied into the non-Bayesian algorithm, such as nonlinear iterative least square (NILS) [ 22 ].…”

JIE for a class of MD systems

“…one measurement is not permitted to be assigned to multiple paths related to the same target, which is consistent with the first constraint given in (2). Equation (5) implies that one measurement can be assigned to at most one target-path pair which is consistent with the second constraint given in (2). It can be seen that the problem of finding the solution of the MD-JIE scheme can be solved through the traditional optimisation algorithms applied on the optimisation problem in (3).…”

“…Different from the traditional single-detection systems, where in each scan there is at most one measurement for each target [1,2], multi-detection (MD) systems can generate, in a given scan, multiple simultaneous detections for one target via different propagation paths. The MD systems generally include the over-thehorizon radar (OTHR) systems [3], the forward-based receivers (FBRs) systems [4,5] and the passive coherent location (PCL) systems [6]. Taking the OTHR systems as an example, there exist multiple distinct radar signals scattered from the same target arriving via different propagation paths during a dwell or scan.…”

Joint estimation of target state and ionospheric height bias in over‐the‐horizon radar target tracking

“…Besides, the virtual ionospheric heights can be estimated based on external sources such as beacons or transponders [6, 34], terrain features [35], and forward‐based receivers (FBRs) [36, 37], the prior ionosphere statistical information [38], or the established ionosphere state model [18]. However, the beacon‐assisted method and the FBRs based method only work within the limited zone, whereas the terrain‐assisted method outputs rough results and the FBRs cannot be deployed at will.…”