Radar Tracking System Using Neural Networks
نویسندگان
چکیده
System Identification based on neural networks has become a very important field in research projects. An attempt has been made to use these neural networks based on a simple back propagation algorithm, with some modifications on input/output vectors, to track a moving object such as aircraft. Prediction was also made on the aircraft position, one step ahead in real time. Introduction The capability of neural networks for approximating arbitrary input-output mappings give a simple way to identify unknown dynamic functions in order to predict the needed output one step ahead or more. In a tracking system, measured radar signals mostly have been mixed with additive white noise. In order to filter out or minimize this measured noise on-line and to predict the aircraft position one step ahead, a simple back propagation algorithm has been used. A typical signal process x(t) for the given measurements y(t) are described by file:///C|/Documents%20and%20Settings/Ponn/Desktop/ijcim/past_editions/1998V06N2/radar_1.htm (1 of 10)24/8/2549 8:53:52 RADAR TRACKING SYSTEM USING NEURAL NETWORKS
منابع مشابه
Design of an Intelligent Controller for Station Keeping, Attitude Control, and Path Tracking of a Quadrotor Using Recursive Neural Networks
During recent years there has been growing interest in unmanned aerial vehicles (UAVs). Moreover, the necessity to control and navigate these vehicles has attracted much attention from researchers in this field. This is mostly due to the fact that the interactions between turbulent airflows apply complex aerodynamic forces to the system. Since the dynamics of a quadrotor are non-linear and the ...
متن کاملMaximum Power Point Tracking of the Photovoltaic System Based on Adaptive Fuzzy-Neural Method
The aim of this paper was to present an optimized method in order to use maximum capacity of the photovoltaic panels. In this regard, we presented a method for the maximum power point tracking in the photovoltaic systems by using the neural networks and adaptive controller. In the proposed system, we estimated an error by using neural network. If this error is lower than the allowable systems e...
متن کاملAdaptive Fusion of Inertial Navigation System and Tracking Radar Data
Against the range-dependent accuracy of the tracking radar measurements including range, elevation and bearing angles, a new hybrid adaptive Kalman filter is proposed to enhance the performance of the radar aided strapdown inertial navigation system (INS/Radar). This filter involves the concept of residual-based adaptive estimation and adaptive fading Kalman filter and tunes dynamically the fil...
متن کاملRadar Esm with a What-and-where Fusion Neural Network
A neural network recognition and tracking system is proposed for classification of radar pulses in autonomous Electronic Support Measure systems. Radar type information is combined with position-specific information from active emitters in a scene. Such a What-and-Where fusion strategy is motivated by a similar subdivision of labor in the brain.
متن کاملDiagnosis of brain tumor using image processing and determination of its type with RVM neural networks
Typically, the diagnosis of a tumor is done through surgical sampling, which is more precise with existing methods. The difference is that this is an aggressive, time consuming and expensive way. In the statistical method, due to the complexity of the brain tissues and the similarity between the cancerous cells and the natural tissues, even a radiologist or an expert physician may also be in er...
متن کامل