Research on the feedforward network method of marine radar track

Author

Yonghong, Li ; Qiu Fuxiang ; Guangzhi, Yang

Author_Institution

Dalian Maritime Univ., China

Volume

2

fYear

1998

fDate

1998

Firstpage

1521

Abstract

This paper presents a novel method to solve the problem of smoothing and prediction in real-time in marine radar tracking by means of a feedforward neural network, which is able to deal with any kind of target data. Varying steps are employed in the network training in addition to the momentum factor. Simulation results show that the predictive track error is rapidly convergent and the accuracy of stable tracking is good enough for marine radar data processing, especially for a ship with a speed below 2O nm/h. The network can also track the target in time which takes a sudden turn

Keywords

convergence; feedforward neural nets; learning (artificial intelligence); marine radar; prediction theory; radar computing; radar signal processing; radar theory; radar tracking; real-time systems; smoothing methods; target tracking; convergence; feedforward neural network; marine radar tracking; momentum factor; network training; radar data processing; real-time prediction; simulation; smoothing; stability; target data; target tracking; tracking error; Convergence; Data processing; Feedforward neural networks; Filters; Neural networks; Predictive models; Radar tracking; Signal processing algorithms; Smoothing methods; Target tracking;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing Proceedings, 1998. ICSP '98. 1998 Fourth International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-4325-5

Type

conf

DOI

10.1109/ICOSP.1998.770913

Filename

770913