Search

For meter-wave multiple-input multiple-output (MIMO) radar, the multipath of target echoes may cause severe errors in height measurement, especially in the case of complex terrain where terrain fluctuation, ground inclination, and multiple reflection points exist. Inspired by a sparse array with greater degrees of freedom and low mutual coupling, a height measurement method based on a sparse array is proposed. First, a practical signal model of MIMO radar based on a sparse array is established. Then, the modified multiple signal classification (MUSIC) and maximum likelihood (ML) estimation algorithms based on two classical sparse arrays (coprime array and nested array) are proposed. To reduce the complexity of the algorithm, a real-valued processing algorithm for generalized MUSIC (GMUSIC) and maximum likelihood is proposed, and a reduced dimension matrix is introduced into the real-valued processing algorithm to further reduce computation complexity. Finally, sufficient simulation results are provided to illustrate the effectiveness and superiority of the proposed technique. The simulation results show that the height measurement accuracy can be efficiently improved by using our proposed technique for both simple and complex terrain. [ABSTRACT FROM AUTHOR]

Aiming at the problem that the overlapping of multipath signals seriously affects the radar's performance of the elevation angle estimation for low‐altitude targets, the authors combine the unitary ESPRIT (UESPRIT) and the multi‐input and multi‐output (MIMO) radar system and propose an algorithm based on UESPRIT to estimate the direction of arrival for low‐altitude targets. Firstly, the virtual matrix after generalised matched filtering of MIMO radar multipath received signals is vectorised. Secondly, for the coherence of direct and reflected wave signals, which cannot be directly processed by the UESPRIT algorithm, the signal preprocessing is performed by spatial smoothing of the sampled data matrices. Finally, the low‐altitude target estimation is carried out by using the UESPRIT algorithm. The Cramer–Rao bound (CRB) for arbitrary unbiased estimation of angle estimation is derived. The relationship between the estimation performance of the algorithm and the signal‐to‐noise ratio, the number of snapshots and the number of elements is analysed by simulation and compared with CRB. The simulation results show that the algorithm can still effectively estimate the elevation angle of low‐altitude targets under the mutual weakening of direct and multipath reflection signals, and has better performance for low‐altitude targets than generalised MUSIC. [ABSTRACT FROM AUTHOR]

Due to suppression jamming by jammers, the signal-to-interference-plus-noise ratio (SINR) during tracking tasks is significantly reduced, thereby decreasing the target detection probability of radar systems. This may result in the interruption of the target track. To address this issue, we propose a multi-static radar power allocation algorithm that enhances the detection and tracking performance of multiple radars in relation to their targets by optimizing power resource allocation. Initially, the echo signal model and measurement model of multi-static radar are formulated, followed by the derivation of the Bayesian Cramér–Rao lower bound (BCRLB). The multi-objective optimization method is utilized to establish the objective function for joint tracking and detection, with dynamic adjustment of the weight coefficient to balance the tracking and detection performance of multiple radars. This ensures the reliability and anti-jamming capability of the multi-static radar system. Simulation results indicate that the proposed algorithm can prevent the interruption of jammer tracking and maintain robust tracking performance. [ABSTRACT FROM AUTHOR]

Implementing an interactive mixed reality simulation system is an economical and risk‐free method for skill training. However, research to enhance the accuracy of mixed reality simulation has always been a challenge. One of the key indicators of a simulation's accuracy is the user's depth perception. Adding depth cues to the simulation scene can effectively increase the accuracy of depth perception. Therefore, in this study, we designed five depth cues to find the one most beneficial for depth perception: (1) depth bar, (2) location ball, (3) fixed window, (4) 3D wireframe, and (5) movable silhouettes. These depth cues were tested using an experimental system with two sets of experimental settings. The first experiment compared the five depth cues at five different viewing distances and showed that the movable silhouettes benefited depth perception accuracy the most. The second experiment compared depth perception accuracies among three different horizontal tilt settings, showing that depth perception accuracy is dependent on the horizontal tilt. Furthermore, different depth perception accuracies were obtained with and without depth cues, proving that the effects from the horizontal tilts were independent of depth cues. The results of these studies provide references for designing interactive mixed reality simulation systems. [ABSTRACT FROM AUTHOR]