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The sensor management problem can be expressed as obtaining the state estimation with desired accuracy by utilizing the resources effectively. In the literature, there are two principal approaches to this problem, namely task-driven and information driven sensor management. Performance metrics for both task-driven and information driven sensor management frameworks suffer from the heavy computational burden due to the evaluation of expectations or are available only in simulation. In this paper, the Observed Information Matrix (OIM), which is widely used in statistical practice as a surrogate for the Fisher Information Matrix (FIM) in difficult problems, has been proposed as a metric that can be used in sensor management. Recursive computation of OIM has been derived for the cases with linear and nonlinear system dynamics corrupted with additive Gaussian noise. The usefulness of OIM in sensor selection in multistatic target tracking has been demonstrated via simulations. [ABSTRACT FROM AUTHOR]

Standard tracking filters perform target detection process by comparing the sensor output signal with a predefined threshold. However, selecting the detection threshold is of great importance and a wrongly selected threshold causes two major problems. The first problem occurs when the selected threshold is too low which results in increased false alarm rate. The second problem arises when the selected threshold is too high resulting in missed detection. Track-before-detect (TBD) techniques eliminate the need for a detection threshold and provide detecting and tracking targets with lower signal-to-noise ratios than standard methods. Although TBD techniques eliminate the need for detection threshold at sensor's signal processing stage, they often use tuning thresholds at the output of the filtering stage. This paper presents a Continuous Wavelet Transform (CWT) and Hidden Markov Model (HMM) based target detection method for employing with TBD techniques which does not employ any thresholding. [ABSTRACT FROM AUTHOR]

This paper presents a channel-adaptive video streaming scheme which adjusts video bit rate according to channel conditions and transmits video through a hybrid RF/free space optical (FSO) laser communication system. The design criteria of the FSO link for video transmission to 2.9 km distance have been given and adaptive bit rate video streaming according to the varying channel state over this link has been studied. It has been shown that the proposed structure is suitable for uninterrupted transmission of videos over the hybrid wireless network with reduced packet delays and losses even when the received power is decreased due to weather conditions. [ABSTRACT FROM AUTHOR]

In free-space optical communication between mobile terminals relative motion of the terminals requires an active mechanism to maintain optical alignment between the stations. Cooperative optical beam tracking could be used to address this problem. In this alignment scheme, each station tracks the arrival direction of its impinging beam to employ it as a guide to precisely point its own beam toward the opposite station. Tracking is achieved at each station by a quadrant photodetector which generates simultaneous azimuth and elevation error voltages. In this study a Kalman filtering assisted cooperative optical beam tracking has been proposed and its suitability to cooperative beam tracking is discussed. In this method, Kalman filter is employed to predict the alignment error that is used to produce appropriate control signals for re-alignment. Performance of the proposed method has been demonstrated through simulations. [ABSTRACT FROM AUTHOR]