Thresholding optimization of global navigation satellite system acquisition with constant false alarm rate detection using metaheuristic techniques.
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| Title: | Thresholding optimization of global navigation satellite system acquisition with constant false alarm rate detection using metaheuristic techniques. |
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| Authors: | Hassani, Mohamed Fouad1 (AUTHOR), Toumi, Abida1 (AUTHOR), Benkrinah, Sabra2 (AUTHOR) s.benkrinah@gmail.com, Sbaa, Salim1 (AUTHOR) |
| Source: | International Journal of Communication Systems. Dec2024, Vol. 37 Issue 18, p1-17. 17p. |
| Subjects: | Global Positioning System, Constant false alarm rate (Data processing), Probability density function, Monte Carlo method, Simulated annealing, Doppler effect, Metaheuristic algorithms, Exponential sums, Rayleigh model |
| Abstract (French): | Summary: In this paper, the enhancement of global navigation satellite system (GNSS) adaptive acquisition using metaheuristic optimization techniques is proposed. The principal goal of this work is to optimize the cell averaging constant false alarm rate (CA‐CFAR) thresholding in Rayleigh fading channels. In GNSS acquisition, pilot and data blocks may have different thresholds. Thus, the optimization will focus on two scaling factors (T1 and T2). Two fusion rules have been used here ("AND" and "OR"). Due to their performances in different optimization problems, metaheuristics have been chosen to be our tool for solving this kind of problem. Simulation results show that the optimized thresholds have an important influence on the performance of the acquisition system. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | Summary: In this paper, the enhancement of global navigation satellite system (GNSS) adaptive acquisition using metaheuristic optimization techniques is proposed. The principal goal of this work is to optimize the cell averaging constant false alarm rate (CA‐CFAR) thresholding in Rayleigh fading channels. In GNSS acquisition, pilot and data blocks may have different thresholds. Thus, the optimization will focus on two scaling factors (T1 and T2). Two fusion rules have been used here ("AND" and "OR"). Due to their performances in different optimization problems, metaheuristics have been chosen to be our tool for solving this kind of problem. Simulation results show that the optimized thresholds have an important influence on the performance of the acquisition system. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 10745351 |
| DOI: | 10.1002/dac.5938 |
