No abstract

The global optimization of sensor locations and a sensitivity analysis based on the minimization of interferences due to wireless communications between sensors are studied in the presence of additive white Gaussian noise (AWGN). We used a Gram matrix approach for robust determination of sensor locations by minimizing the interferences (maximizing the signal strength) among sensors for engine health monitoring systems. In order to solve the problem of optimum placement, an iterative algorithm for maximizing the determinant of the Gram matrix is proposed and implemented. The sensitivity criterion proposed in this paper is the spectral number of the Frobenius norm of the Gram matrix associated with sensor readings. We derived the necessary conditions under which the number of sensors and the optimal sensor locations will remain unchanged when the data measured for sensitivity analysis is affected by AWGN. Our theoretical results are verified by simulations providing details concerning numerical implementations.

In previous papers we solved the problem of the sensor location optimization based on the minimization of interferences due to wireless communications between sensors. We assumed that each sensor has wireless communication capabilities, in that each sensor reading is characterized in terms of signal to noise ratio. In this paper we extend the previous work in the system of systems context by studying the robustness of the optimized sensor location in the presence of white additive Gaussian Noise (AWGN). We address the question on weather the optimized sensor locations remain the same if the initial reading sensors are only affected by additive white Gaussian noise (AWGN). The analysis results are verified trough computer simulations.

Location technologies constitute an essential component of systems design for autonomous operations and control. The Global Positioning System (GPS) works well in outdoor areas, but the satellite signals are not strong enough to penetrate inside most indoor environments. As a result, a new strain of indoor positioning technologies that make use of 802.11 wireless LANs (WLAN) appeared. Contemporary WLAN positioning maintains the database of location fingerprints which is used to identify the most likely match of incoming signal data with those preliminary surveyed and saved in the database. An issue with these systems, however, is the operation robustness. This paper investigates the issue of deploying WLAN positioning software on mobile platforms and studies an integrity monitoring technique to account for unstable signal characteristics, which are often observable in WLAN. Integrity monitoring algorithms can handle the redundancy of APs to identify "rogue" ones, isolate them and improve system robustness.