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DOA estimation for local scattered CDMA signals by particle swarm optimization.

Chang JC - Sensors (Basel) (2012)

Bottom Line: For conventional spectral searching estimators with local scattering, the searching complexity and estimating accuracy strictly depend on the number of search grids used during the search.In this paper, a modified PSO is presented to reduce the required search grids for the conventional spectral searching estimator with the effects of local scattering.Finally, several computer simulations are provided for illustration and comparison.

View Article: PubMed Central - PubMed

Affiliation: Department of Information Technology, Ling Tung University, Taichung 408, Taiwan. changjc@mail.ltu.edu.tw

ABSTRACT
This paper deals with the direction-of-arrival (DOA) estimation of local scattered code-division multiple access (CDMA) signals based on a particle swarm optimization (PSO) search. For conventional spectral searching estimators with local scattering, the searching complexity and estimating accuracy strictly depend on the number of search grids used during the search. In order to obtain high-resolution and accurate DOA estimation, a smaller grid size is needed. This is time consuming and it is unclear how to determine the required number of search grids. In this paper, a modified PSO is presented to reduce the required search grids for the conventional spectral searching estimator with the effects of local scattering. Finally, several computer simulations are provided for illustration and comparison.

No MeSH data available.


Normalized output w̅ip(k) versus normalized input zip(k) / θmax under wmin = 0.
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f1-sensors-12-03228: Normalized output w̅ip(k) versus normalized input zip(k) / θmax under wmin = 0.

Mentions: In Equation (21), wmin be added to avoid particles from stopping moving. The curves of wip(k) with wmin = 0 using different μ can be plotted in Figure 1. Then, we also investigate the sensitivity for APSO-GMUSIC with different values of μ However, it accords with our strategy for different μ. Thus, μ-law algorithm with μ = 100 is chosen. Note that for every particle in population, wip(k) is unique and can be computed individually. Therefore, the single inertia weight wip(k) can be replaced by a multiple adaptive inertia weight wip(k). The proposed APSO-GMUSIC seems to be robust to control parameters due to the intrinsic advantages of the algorithm and the separation of the problem-independent PSO kernel from newly introduced problem-specific features in our design for adaptive multiple inertia weight. Finally, the steps for implementing the APSO-GMUSIC are shown in Figure 2 and described in the list that follows.


DOA estimation for local scattered CDMA signals by particle swarm optimization.

Chang JC - Sensors (Basel) (2012)

Normalized output w̅ip(k) versus normalized input zip(k) / θmax under wmin = 0.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3376592&req=5

f1-sensors-12-03228: Normalized output w̅ip(k) versus normalized input zip(k) / θmax under wmin = 0.
Mentions: In Equation (21), wmin be added to avoid particles from stopping moving. The curves of wip(k) with wmin = 0 using different μ can be plotted in Figure 1. Then, we also investigate the sensitivity for APSO-GMUSIC with different values of μ However, it accords with our strategy for different μ. Thus, μ-law algorithm with μ = 100 is chosen. Note that for every particle in population, wip(k) is unique and can be computed individually. Therefore, the single inertia weight wip(k) can be replaced by a multiple adaptive inertia weight wip(k). The proposed APSO-GMUSIC seems to be robust to control parameters due to the intrinsic advantages of the algorithm and the separation of the problem-independent PSO kernel from newly introduced problem-specific features in our design for adaptive multiple inertia weight. Finally, the steps for implementing the APSO-GMUSIC are shown in Figure 2 and described in the list that follows.

Bottom Line: For conventional spectral searching estimators with local scattering, the searching complexity and estimating accuracy strictly depend on the number of search grids used during the search.In this paper, a modified PSO is presented to reduce the required search grids for the conventional spectral searching estimator with the effects of local scattering.Finally, several computer simulations are provided for illustration and comparison.

View Article: PubMed Central - PubMed

Affiliation: Department of Information Technology, Ling Tung University, Taichung 408, Taiwan. changjc@mail.ltu.edu.tw

ABSTRACT
This paper deals with the direction-of-arrival (DOA) estimation of local scattered code-division multiple access (CDMA) signals based on a particle swarm optimization (PSO) search. For conventional spectral searching estimators with local scattering, the searching complexity and estimating accuracy strictly depend on the number of search grids used during the search. In order to obtain high-resolution and accurate DOA estimation, a smaller grid size is needed. This is time consuming and it is unclear how to determine the required number of search grids. In this paper, a modified PSO is presented to reduce the required search grids for the conventional spectral searching estimator with the effects of local scattering. Finally, several computer simulations are provided for illustration and comparison.

No MeSH data available.