A Hybrid Genetic Optimization Method for Accurate Target Localization
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2018
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Scientific Technical Review
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This paper considers the problem of estimating the position of a target based on the time of arrival (TOA) measurements from a set of receivers whose positions are known. The weighted least square (WLS) technique is applied as an efficient existing approach. The optimization problem is formulated by the minimization of the sum of squared residuals between estimated and measured data as the objective function. The hybrid Genetic Algorithm-Nelder-Mead (GA-NM) method is proposed that combines the global search and local search abilities in an effective way in order to improve the performance and the solution accuracy. The corresponding Cramer-Rao lower bound (CRLB) on the localization errors is derived as a benchmark. Simulation results show that the proposed hybrid GA-NM method achieves a significant performance improvement compared to existing methods
Keywords:
receiver / localization / optimization / genetic algorithm / hybrid methodSource:
Scientific Technical Review, 2018, 68, 3, 50-55Publisher:
- Belgrade : Military Technical Institute
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Mašinski fakultetTY - JOUR AU - Rosić Vitas, Maja AU - Simić, Mirjana AU - Pejović, Predrag V. PY - 2018 UR - https://machinery.mas.bg.ac.rs/handle/123456789/6037 AB - This paper considers the problem of estimating the position of a target based on the time of arrival (TOA) measurements from a set of receivers whose positions are known. The weighted least square (WLS) technique is applied as an efficient existing approach. The optimization problem is formulated by the minimization of the sum of squared residuals between estimated and measured data as the objective function. The hybrid Genetic Algorithm-Nelder-Mead (GA-NM) method is proposed that combines the global search and local search abilities in an effective way in order to improve the performance and the solution accuracy. The corresponding Cramer-Rao lower bound (CRLB) on the localization errors is derived as a benchmark. Simulation results show that the proposed hybrid GA-NM method achieves a significant performance improvement compared to existing methods PB - Belgrade : Military Technical Institute T2 - Scientific Technical Review T1 - A Hybrid Genetic Optimization Method for Accurate Target Localization EP - 55 IS - 3 SP - 50 VL - 68 DO - 10.5937/str1803050r ER -
@article{ author = "Rosić Vitas, Maja and Simić, Mirjana and Pejović, Predrag V.", year = "2018", abstract = "This paper considers the problem of estimating the position of a target based on the time of arrival (TOA) measurements from a set of receivers whose positions are known. The weighted least square (WLS) technique is applied as an efficient existing approach. The optimization problem is formulated by the minimization of the sum of squared residuals between estimated and measured data as the objective function. The hybrid Genetic Algorithm-Nelder-Mead (GA-NM) method is proposed that combines the global search and local search abilities in an effective way in order to improve the performance and the solution accuracy. The corresponding Cramer-Rao lower bound (CRLB) on the localization errors is derived as a benchmark. Simulation results show that the proposed hybrid GA-NM method achieves a significant performance improvement compared to existing methods", publisher = "Belgrade : Military Technical Institute", journal = "Scientific Technical Review", title = "A Hybrid Genetic Optimization Method for Accurate Target Localization", pages = "55-50", number = "3", volume = "68", doi = "10.5937/str1803050r" }
Rosić Vitas, M., Simić, M.,& Pejović, P. V.. (2018). A Hybrid Genetic Optimization Method for Accurate Target Localization. in Scientific Technical Review Belgrade : Military Technical Institute., 68(3), 50-55. https://doi.org/10.5937/str1803050r
Rosić Vitas M, Simić M, Pejović PV. A Hybrid Genetic Optimization Method for Accurate Target Localization. in Scientific Technical Review. 2018;68(3):50-55. doi:10.5937/str1803050r .
Rosić Vitas, Maja, Simić, Mirjana, Pejović, Predrag V., "A Hybrid Genetic Optimization Method for Accurate Target Localization" in Scientific Technical Review, 68, no. 3 (2018):50-55, https://doi.org/10.5937/str1803050r . .