Abstract
With the fast development of new array technology and intelligent antenna, it is easier to obtain angle of arrival (AOA) measurements. Hybrid received signal strength (RSS) and AOA measurement techniques are proposed for the position computing in sensor networks. By converting the measurement equations and relaxing the optimization function, range-based square semidefinite programming (RLS-SDP) and squared range-based square semidefinite programming (SRLS-SDP) algorithms are put forward to obtain the source position estimate by considering the transmit power to be known or unknown. The proposed RLS-SDP and SRLS-SDP algorithms provide accurate solution to the source position estimate and avoid the initialization process of numerical calculation. The simulations show that the proposed RLS-SDP and SRLS-SDP algorithms perform better than the linear estimator and provide the accuracy performance which is very close to the Cramer-Rao Lower Bound (CRLB) of position estimation. The proposed SRLS-SDP algorithm shows its advantages in the computational complexity compared with the RLS-SDP, since the complexity of SRLS-SDP is independent of the number of anchor nodes.
Highlights
Sensor network has been playing a key role in many applications, such as surveillance, emergency services, friend finding, and tracking of the elderly [1]–[5]
In a 3-dimensional space, four anchor nodes are randomly placed at the positions listed in Tab. 2
The true transmit power p0 is randomly drawn from the range [−40, −50] dB
Summary
Sensor network has been playing a key role in many applications, such as surveillance, emergency services, friend finding, and tracking of the elderly [1]–[5]. When the transmit powers are unavailable and assumed to be unknown, the RSS-based scheme is designed to estimate the positions of the source nodes in [44]. By relaxing the non-convex optimization problem into the convex optimization, the proposed RLS-SDP and SRLS-SDP algorithms provide a solution for the source position estimate and avoid the initialization of the numerical calculation. The main contributions of this paper are listed as follows, 1) By exploiting the correlation between RSS and AOA measurements, weighted least square (WLS) solution is proposed to obtain the source position estimate. 2) When the transmit power is unavailable and assumed to be an unknown parameter, the RLS-SDP and SRLS-SDP algorithms are redesigned by relaxing the optimization problem into convex form. For arbitrary symmetric matrix A, A 0 means that A is positive semidefinite
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