Maximum Likelihood DOA Estimation with Sensor Position Perturbation Using Particle Swarm Optimization

  • Jhih-Chung Chang
  • Chia-Yi Chen
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 20)


In this paper, we consider the problem of direction-of-arrival (DOA) estimation for code-division multiple access (CDMA) signals in the presence of sensor position errors. For array calibration with sensor position errors, the estimation of the source directions and unknown array parameters is essential. The cost function is an extension of the maximum likelihood (ML) criteria that was originally developed for DOA estimation with a perfectly calibrated array. It is shown that the ML function is a complicated nonlinear multimodal function over a high-dimensional problem space. A modified particle swarm optimization (PSO) is proposed to compute the ML functions and find the global minimum cost function for array calibration. This proposed method has no requirement for calibration sources while the sensor position errors as well as the DOA of the incident signals can be estimated at the same time. Simulation results show that the proposed estimator has better performance over other popular methods.




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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of Information TechnologyLing Tung UniversityTaichungTaiwan, ROC
  2. 2.Institute of Applied Information TechnologyLing Tung UniversityTaichungTaiwan, ROC

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