Sanagapallea Koteswara Rao

Bio: Sanagapallea Koteswara Rao is an academic researcher from K L University. The author has contributed to research in topics: Covariance & Monte Carlo method. The author has co-authored 1 publications.

Measure of Nonlinearity With Application to Bearings-Only Target Tracking

Abstract: Using the recently proposed measure of nonlinearity (MoN), the authors try to find the magnitude of nonlinearity for passive target tracking with bearings-only measurements in underwater environment. The method derived to measure the nonlinearity is completely based on the state covariance matrices of the filters. It is tried to find the allowable magnitude of nonlinearity in terms of MoN with which a filter can perform to estimate the target motion parameters with required accuracy. In this paper, MoN values for different filters are computed for different scenarios. Results obtained in the Monte Carlo simulation are presented.

UAV-to-Ground Target Robust Tracking Algorithm Based on Two-Way CNN

Abstract: In order to make the UAV equipment track the ground target accurately in the flight process, this paper proposes a UAV-To-Ground target robust tracking algorithm based on Two-Way CNN. The algorithm is based on two-way CNN architecture, and detects the visual target of UAV after solving the surf feature of the ground target image. According to the linear correction expression of the tracking parameters, the algorithm determines the performance intensity of the non maximum suppression effect of the tracking coefficient on UAV ground target parameters, and then combines the known tracking coefficient and the loss function to realize the tracking of the UAV ground target. The experimental results show that under the effect of the dual CNN network architecture, the tracking accuracy of the UAV equipment for the established ground target during flight is significantly improved, which can meet the actual application requirements.