IEEE Access · 2018 · 26 citations · 29 references
EngineeringComputational EngineeringOptimizationSensor FusionSensorsAcoustic LocalizationDigital Signal ProcessingLocalization UncertaintyWireless Sensor NetworksBest Linear Unbiased EstimationLocation EstimationPositionSemidefinite ProgrammingSemidefinite Programming RelaxationSemidefinite RelaxationSource LocalizationSource Position Estimation
In this paper, the Doppler frequency shift-based localization problem in the presence of sensor location errors is addressed. Based on the measurement model, we present two methods, an explicit solution and a semidefinite relaxation (SDR) technique, to estimate the position of the stationary source. In the two proposed algorithms, the non-accurate information on sensor position and velocity is considered. In the former algorithm, based on two best linear unbiased estimator, an explicit solution of the source position can be obtained, whereas in the latter one, the SDR technique is applied to relax the original maximum likelihood estimation into a convex semidefinite programming problem, which provides accurate estimate without postprocessing. Compared with the methods where the sensor location errors are not taken into consideration, the proposed algorithms are able to achieve a more accurate localization result. Simulations verify a better performance of these two proposed algorithms.
29
Semidefinite Relaxation of Quadratic Optimization Problems
Zhi‐Quan Luo, Wing‐Kin Ma, Anthony Man–Cho So et al. · IEEE Signal Processing Magazine · 2010 · 3.6K citations
A simple and efficient estimator for hyperbolic location
Y.T. Chan, K. C. Ho · IEEE Transactions on Signal Processing · 1994 · 2.5K citations
Engineering, Radiology, Antennas +12