Optimized processing of satellite signal via evolutionary search algorithm
Researchers from the Satellite Navigation Research Group (SNAG) of UTM are currently conducting a research program that mitigates the effect of the Anti-Spoofing (AS) policy. A robust strategy, called the Pseudo Randomized Search Strategy (PRSS) has been developed to counter the effect of this AS po...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
2000
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/2308/1/Hassan2000__OptimizedProcessingofSatelliteSignal.pdf http://eprints.utm.my/id/eprint/2308/ |
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| Summary: | Researchers from the Satellite Navigation Research Group (SNAG) of UTM are currently conducting a research program that mitigates the effect of the Anti-Spoofing (AS) policy. A robust strategy, called the Pseudo Randomized Search Strategy (PRSS) has been developed to counter the effect of this AS policy. The PRSS algorithm is an adaptive search technique that can learn a high performance knowledge structure in reactive environments that provide information as an objective function. A combination of three methods, namely optimization, global random search and ambiguity function mapping has produced an efficient and robust mitigation technique. Numerical results indicate that, in all the test cases, no more than 4% search of the total search space was investigated to determine the correct set of answers. This result implies that the size of the search window does not play an important role in determining the search efficiency. This will take away the constraint resulted from the AS policy in processing the GPS satellites signal. The algorithm also shows its robustness because it does not require a good initial starting point. Using a different initial point, all of them produced the correct results |
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