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2023, Volume 24, Issue 8

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Frontiers of Information Technology & Electronic Engineering >> 2023, Volume 24, Issue 8 doi: 10.1631/FITEE.2200260

High-accuracy target tracking for multistatic passive radar based on a deep feedforward neural network

武汉大学电子信息学院，中国武汉市，430072

Received: 2022-06-17 Accepted: 2023-08-29 Available online: 2023-08-29
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Abstract

In radar systems, errors are mainly from motion models and nonlinear measurements. When we evaluate a tracking algorithm, its is the main criterion. To improve the , in this paper we formulate the tracking problem into a regression model from measurements to target states. A tracking algorithm based on a modified (MDFNN) is then proposed. In MDFNN, a is introduced to describe the temporal sequence relationship of the input measurement sequence, and the optimal measurement sequence size is analyzed. Simulations and field experimental data of the show that the accuracy of the proposed algorithm is better than those of extended Kalman filter (EKF), unscented Kalman filter (UKF), and recurrent neural network (RNN) based tracking methods under the considered scenarios.

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