Target Prioritization for Multi-Function Radar Using Artificial Neural Network Based on Steepest Descent Method
Nam-Hoon Jeong, Seong‐Hyeon Lee, Minseok Kang, Chang-Woo Gu, Cheol‐Ho Kim, Kyung-Tae Kim · The Journal of Korean Institute of Electromagnetic Engineering and Science · 2018
Target prioritization is necessary for a multifunction radar(MFR) to track an important target and manage the resources of the radar platform efficiently. In this paper, we consider an artificial neural network(ANN) model that calculates the priority of the target. Furthermore, we propose a neural network learning algorithm based on the steepest descent method, which is more suitable for target prioritization by combining the conventional gradient descent method. Several simulation results show that the proposed scheme is much more superior to the traditional neural network model from analyzing the training data accuracy and the output priority relevance of the test scenarios.