Papers by Keyword: Distributed Detection

Abstract: In this paper, we consider the problem of local power constrained coherent distributed detection over fading multi-access channel (MAC). The deflection coefficient maximization (DCM) is used to optimize the performance of fusion system under local power constraint of sensors. We use the statistical information of channel gain to obtain the deflection coefficient of the detection statistics at the fusion center. We derive the closed-form solution to the considered optimization problem. Monte-Carlo simulations are carried out to verify the performance of the proposed method. Simulation results show that the proposed method could significantly improve the detection performance of the fusion system under local power constraint and low signal-to-noise ratio (SNR).

Abstract: With the increasing rapid development of China's economy and people's requirements for living water’s quality becoming higher and higher, the safety and sustainability of water resources development becomes increasingly important. Traditional automatic detection system of water resource based on wireless station and GPRS terminal can not meet the needs of detection. In view of this situation，A water resource distributed detection system based on cloud computing technology takes full advantages of cloud computing in management and services, improves efficiency and saves operating cost of the water source detection.

Abstract: In order to improve the detection performance of distributed detection system under noisy fading channel, two analog transmission schemes, i.e. an analog transmission and a modified analog transmission, were proposed. Simulations show that, when the channel SNR is high, such as larger than 20dB, the system with the proposed analog transmission scheme can approach that with ideal transmission condition in detection performance. For low channel SNR, such as less than 10dB, the modified analog transmission scheme results in better detection performance than the binary transmission scheme proposed in literature. Therefore, according to the channel state information at the sensor, the sensor can select appropriate transmission scheme to improve the system’s detection performance.

Abstract: This paper proposes an optimization algorithm which combines climb algorithm and ant algorithm and use it to solve optimization problems of fusion rules in distributed detection systems .Firstly, algorithm takes Bayes risk as the cost function, uses Climb-ant algorithm to optimize the sensors' decision threshold and Bayes criteria to solve the fusion rules of fusion center. Ultimately, we get the system's optimal (or suboptimal) fusion rules and realize the optimization of fusion rules in distributed detection system. Theoretical analysis and experimental results show that the new method has higher accuracy and efficiency of the solution than the traditional MAP (maximum a posteriori), SA-MAP, GA-MAP, and Coordinate Rotation Method.

Abstract: The need for mobility and the rapid deployment motivates the research of distributed radar sensor network with N_T transmitters, N_R receivers and a fusion center, where the fusion center and the receivers are communicated via wireless signaling. With the assumption of orthogonal waveforms for sensing and circular complex Gaussian noise channel model for communication, the formulae of detection probability and the false alarm probability are derived given the sensing power and communication power. Numerical results show that with the increase of the total power, the ratio between the best sensing power and the best communication power will increase. Moreover, the shape of the region in which the target detection probability is larger than a predetermined value is not regular, which should be taken care in case of network planning.

Abstract: The ant colony optimization algorithm is good at solving multidimensional optimization problem. The allocation of power resource of a node in wireless sensor networks should make the detection performance of the whole network maximum, which is complex due to the detection probability of the whole system cannot be expressed explicitly. Therefore, continuous ant colony system (CACS) is adopted to optimize the allocation of each node’s power between sensing and communications. The results show that it can lead to a good power allocation. At the same time, the scheme that all sensor nodes have identical power assignment can achieve nearly the same detection performance as compared that achieved by the best scheme searched by CACS. As a result, particu-larly for a large number of sensors, an identical power allocation scheme for each node can be employed to achieve nearly the best detection performance.

Abstract: In this paper, the signal detection problem when distributed sensors are used a global decision is desired is considered. Local decisions from the sensors are fed to the data fusion center which then yields a global decision based on a fusion rule. Based on The data fusion theories of Bayesian criterion used for a distributed parallel structure, fusion rules at the fusion center、 the decision rules of sensors and the results of the computer simulation for two identical sensors, two different sensors and three identical sensors are presented. The results of the computer simulation show that the performance of the fusion system, compared with the sensor, has been improved. For the case there are three identical sensors in the fusion system, Bayesian risk is reduced by 26.5%, compared with the sensor.