Abstract
Problem statement: This study unveils the potential and utilization of Neural Network (NN) in radar applications for target classification. The radar system under test is a special of it kinds and known as Forward Scattering Radar (FSR). In this study the target is a ground vehicle which is represented by typical public road transport. The features from raw radar signal were extracted manually prior to classification process using Neural Network (NN). Features given to the proposed network model are identified through radar theoretical analysis. Multi-Layer Perceptron (MLP) back-propagation neural network trained with three back-propagation algorithm was implemented and analyzed. In NN classifier, the unknown target is sent to the network trained by the known targets to attain the accurate output. Approach: Two types of classifications were analyzed. The first one is to classify the exact type of vehicle, four vehicle types were selected. The second objective is to grouped vehicle into their categories. The proposed NN architecture is compared to the K Nearest Neighbor classifier and the performance is evaluated. Results: Based on the results, the proposed NN provides a higher percentage of successful classification than the KNN classifier. Conclusion/Recommendation: The result presented here show that NN can be effectively employed in radar classification applications.
Highlights
In the Radar System, if the transmitter and receiver are collocated, this configuration is known as a monostatic radar system[1]
The result presented shows that neural networks can be effectively employed in Forward Scattering Radar (FSR) as an automatic classifier
The three layer Multi-Layer Perceptron (MLP) neural network structure that we have built gave very promising results in vehicle recognition and vehicle categorization. 10% of overall data was misclassified in vehicle recognition and only 2% of overall data was misclassified in vehicle categorization
Summary
In the Radar System, if the transmitter and receiver are collocated, this configuration is known as a monostatic radar system[1]. Before and during World War II, a so called ‘forward scatter fence’ was used for aircraft detection and almost 200 of these fences were deployed by France, Japan and The Soviet Union[2] These were bistatic radars, but their geometry was similar to the forward scatter configuration, where targets fly near the transmitter-receiver baseline. These radars used Continuous Wave (CW) transmitters, so the receiver detected a beat frequency produced between the direct signal from the transmitter and the Doppler frequency shift scattered by the moving target. Most of the early forward scatter fences were eventually replaced by monostatic radars which have better spatial coverage area and location accuracy
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