Doppler Information Optimization through Fusion Algorithms

Doppler Information Optimization through Fusion Algorithms

This paper analyses the velocity estimation of a target, from the Doppler filter using 1) Kalman filter 2) Adaptive Kalman filter 3) Kalman filter with state vector fusion 4) Adaptive Kalman filter with state vector fusion 5) State vector fused adaptive Kalman filter. Simulation through MATLAB gave good response for 4 and 5 algorithms under low signal to noise ratio. 2 and 3 algorithms gave bet...

A Risk Profile for Information Fusion Algorithms

E.T. Jaynes, originator of the maximum entropy interpretation of statistical mechanics, emphasized that there is an inevitable trade-off between the conflicting requirements of robustness and accuracy for any inferencing algorithm. This is because robustness requires discarding of information in order to reduce the sensitivity to outliers. The principal of nonlinear statistical coupling, which ...

Discovering Optimization Algorithms Through Automated Learning

In this paper, we describe the supervised learning approach to optimization problems in the spirit of the PAC learning model. By this approach, we discover domain-specific algorithms by learning from an oracle, which is also an optimization algorithm for the problem in question. We describe examples of learning backtracking-based algorithms and algorithms that implement the dynamic programming ...

Information Utilization Ratio in Heuristic Optimization Algorithms

Heuristic algorithms are able to optimize objective functions efficiently because they use intelligently the information about the objective functions. Thus, information utilization is critical to the performance of heuristics. However, the concept of information utilization has remained vague and abstract because there is no reliable metric to reflect the extent to which the information about ...

Design Algorithms for Doppler MTI and Filters (Using Chebyshev Approximation)