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Using fractal dimension or one of other fractal characteristics to detect targets in sea clutter, it is often difficult to distinguish at low signal-to-clutter ratios. To solve this problem, a new method for target detection in sea clutter based on combined fractal characteristics is proposed. The detection process is divided into two stages: coarse detection and fine detection. When the fractal spectrum...
In this paper, a plain data-driven and simulation-based approach to object tracking is investigated. The basic idea is to use the probabilistic model of the tracking problem to simulate a large amount of state and observation sequences. Both are fed into a regression algorithm that learns a mapping from the observations to the states. In particular, we consider random forest regression and apply it...
Considering the convergence rate is a very important issue as distributed sensors networks usually consist of low-powered wireless devices and speeding up the consensus convergence rate is also important to reduce the number of messages exchanged among neighbors, a new adaptive method for weight assignment of communication links between sensor nodes is proposed based on the dynamic network topology...
In this paper, under the situation of multiple interference regions, an optimal antenna placement problem for a distributed Multi-Input Multi-Output (MIMO) radar is studied. Considering multiple interference regions, we solve the antenna placement problem by utilizing antenna placement method based on Multi-Objective Particle Swarm Optimization (MOPSO). However, it is not clear when to stop the iteration...
In this paper, we consider different approaches in reducing the amount of data transfer in a distributed Kalman filtering based on noisy linear observations. The observations are either compressed using equivalent measurements, or transmitted only if their values change more than a specified value. The objective is to reduce sensor data traffic with relatively small estimation performance degradation...
In this paper, a joint revisit and dwell time management (JRDTM) strategy for single target tracking based on the predicted Bayesian Cramer-Rao lower bound (BCRLB) in phased array radar system is addressed. We achieve the time resources management by formulating and solving an optimization problem, which is to minimize the resource amount used for tracking with the tracking accuracy of the target...
In this paper, we will investigate a joint beam and dwell time allocation strategy for multiple targets tracking based on the phased array radar system. We achieve the resources allocation by formulating and solving an optimization problem, which is to minimize the total dwell time on all targets with the tracking accuracy of each target satisfying a pre-designed requirement. Since the Bayesian Cramer-Rao...
Automated recognition of spacecraft and space debris using imaging plays an important role in securing space safety and space exploration. Although deep learning is now the most successful solution for image-based object classification, it requires a myriad number of training data, which are not available for most real applications. In this paper, we investigate different single and hybrid data augmentation...
In order to reduce the effects caused by complex environments and ambient light conditions, a fast, robust and effective obstacles detection method of vehicles based on image analysis of multi-feature is proposed. Firstly, regions of interest (ROI) which contain lanes, vehicles and few parts of interference background are extracted in the input image by detecting gradient feature in rows. Secondly,...
We present a particle filter for multi-object tracking that is based on the ideas of the Approximate Bayesian Computation (ABC) paradigm. The main idea is to avoid the explicit computation of the likelihood function by means of simulation. For this purpose, a large amount of particles in the state space is simulated from the prior, transformed into measurement space, and then compared to the real...
Autonomous navigation for spacecraft is not possible using two-way tracking today, but it is crucial during critical event such as when a spacecraft inserts into orbit around a planet in deep space exploration. As the Deep Space Atomic Clock (DSAC) diminishes in size and increases in stability, the accuracies of one-way radiometric observations are improved and can reach the demands of onboard one-way...
We propose a diffusion expectation-maximization algorithm with adaptive combiner for distributed estimation over sensor networks. Due to the spatial distribution of the nodes, variation of node profile across the network is a common phenomena in real applications. The unreliable nodes exist and provide inaccurate estimates, which may be caused by high levels of noise or malicious attacks. Instead...
A bias-compensated normalized least mean absolute deviation (NLMAD) algorithm is developed for system identification under impulsive output measurement noise and noisy input environment, which takes the advantage of the NLMAD to resist impulsive output noises. Considering biased estimation caused by the noisy input, we employ an unbiasedness criterion to obtain a bias-compensated vector for NLMAD...
In this paper, a novel quaternion adaptive filtering algorithm is proposed for a unified processing of 3D and 4D data, called quaternion least mean kurtosis (QLMK) algorithm. Multi-dimensional signals exhibit a complex nonlinear relationship and couple among different components. Considering that quaternion has huge advantage in terms of the representation of 3D and 4D signal, quaternion algebra is...
This paper considers the detection problem and its realistic implementation for multiple-input multiple-output (MIMO) radar with widely separated antennas. In particular, since the range cells of different transmit-receive channels are not in superposition, but intersecting with each other, it is difficult to determine, by gathering measurements from all transmit-receive channels, whether a target...
Multiple view data with different feature representations have widely arisen in various practical applications. Due to the information diversity, fusing multiview features is very valuable for classification purpose. In this paper, we propose a new multifeature fusion method called fractional-order discriminative multiview correlation projection (FDMCP), which is based on fractional-order scatter...
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