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Semantic segmentation is an important task for autonomous vehicle navigation in off road environments. However, several natural factors make this problem uniquely challenging. For example, road segmentation is often difficult under heavy shadow or steel terrain, and dangerous muddy water puddles may have the similar visual appearance to dirt road surfaces (and thus are hard to identify). To tacule...
This paper considers the multi-target tracking (MTT) problem in multi-input multi-output (MIMO) radar systems with the “defocused transmit-focused receive” (DTFR) operating mode, in which each transmitter forms a defocused beam to illuminate the whole surveillance region and each receiver adopts a focused beam to acquire a high angular resolution. When MIMO radars work in the DTFR operating mode,...
Aiming at the radiation control problem for sensor scheduling, a sensor scheduling algorithm based on partially observable Markov decision process (POMDP) is proposed. The target model is set up in the three-dimensional space, and the tracking task requirement is given by fuzzy logic theory. Then the radiation risk model is formulated as a POMDP, and the sensor radiation risk is dynamic updated by...
Pulsars autonomous navigation is characterized by its credible performance and high navigation accuracy, which will have broad prospects for use in deep-space autonomous navigation. In our study, we find the observation time required for different pulsars to obtain the same time of arrival (TOA) accuracy is different, which means the rates of different sensors are different. However, the previous...
This paper considers the sensor selection problem for target tracking in large-scale sensor networks. We propose a new sensor selection strategy based on dual-criterion optimization. Both the bias change detection and information gain maximization are considered as criteria in our proposed sensor selection strategy. This new approach extends the sensor selection problem from single criterion optimization...
In this paper, we consider the fluctuating targets detection problem in a distributed multi-sensor network. A multi-sensor multi-frame track-before-detect (MS-MF-TBD) procedure is proposed to sufficiently make use of the target energy diversity in space and time dimensions (space-time diversity). Two MS-MF-TBD methods, the multi-sensor maximum likelihood-probabilistic data association (MS-ML-PDA)...
In this paper, we address the target detection problem using multi-sensor dynamic programming based track before detect (DP-TBD) methods. First, we give two implementation methods of multi-sensor DP-TBD under the centralized processing and the distributed processing, respectively. Then, in order to improve the implementation efficiency of the multi-sensor DP-TBD, we further propose an improved DP-TBD...
Atrial Fibrillation (AF) is the most common chronic arrhythmia. Effective detection of the AF would avoid serious consequences like stroke. Conventional AF detection methods need heuristic or hand-craft feature extraction. In this paper, A deep neural network named multi-scale convolutional neural networks (MCNN) based AF detector is proposed. Instant heart rate sequence is extracted from ECG signal,...
In the complex pattern classification problem, the reliability of classifier output for the patterns located at different regions of the data set may be different. In order to efficiently improve the classification accuracy, we propose a new method to correct the original classifier output using the local knowledge of the classifier performance in different regions. The training data set can be divided...
To address multi-sensor robust track-to-track association in the presence of sensor biases and missed detections, where sensors biases is time-varying and non-uniform, the target of different sensors is non-identical, the robust track-to-track association algorithm based on t-distribution mixture model is proposed. The robust track-to-track association problem is turned into the non-rigid point matching...
In this paper, a robust Gaussian filtering is proposed based on M-estimate with adaptive measurement noise covariance. In the proposed method, the M-estimate is incorporated into the Gaussian filtering framework through modifying the measurements residues to introduce robustness. The modified measurements residues are also stored to identify the measurement noise covariance based on Myers-Tapley method...
This paper considers the location and tracking problem for the indoor and outdoor targets with the single input multiple output (SIMO) radar. An effective algorithm based on phase comparison is presented to derive the target azimuth by exploiting the phase differences between the return signals among the multiple channels. In addition, the target range is derived via employing the fast Fourier transform...
A multi-source image registration algorithm based on combined line and point features is proposed for images containing typical line objects. Firstly, the image control line features are extracted for coarse registration by the use of visual saliency and Line Segment Detection (LSD). Visual saliency represents human visual characteristics. LSD has attributes including rotation invariance, illumination...
In this paper, we consider the source localization problem in which several microphones collaborate to locate an active sound source in a reverberant environment. Sound source localization (SSL) based on the Generalized Cross Correlation (GCC) function is widely studied for the past few decades. However, in a reverberant environment, the maximal peak of the GCC function does not necessarily correspond...
It is critical to classify the landing terrain from aerial images when an unmanned aerial vehicle lands at an unprepared site autonomously by using a vision sensor. Owing to the interference of illumination variations and noises, different terrains may show a similar image feature and the same terrain may have a different image feature, which brings great difficulties to image classification. To address...
Doppler radars are low cost and light weight sensors that have a potential to find wide applications in building a large team of mobile vehicle platforms. Because of the nonlinearity associated with the measurement from Doppler radars, it is both interesting and challenging to extract meaningful information from the low cost sensors. Building upon the authors' previous work on self localization with...
In this paper, the problem of robust minimax testing of binary composite hypothesis is considered, while the actual probability densities are located in neighborhoods characterized by the Itakura-Saito divergence. And then the existence of a saddle value condition is proved under Sion's minimax theorem. Moreover, we derive the least favorable distributions and the robust decision rule involved four...
This paper proposes a method of searching for missing people in mountains by UAVs (Unmanned Aerial Vehicles) based on beacon signals. This method alternately updates the distribution of estimated target position and unknown parameters by particle filtering, and determines the next best observation location based on the idea of the uncertainty sampling. We will show how this method can be integrated...
The ball state tracking and detection technology plays a significant role in volleyball game analysis for volleyball team supporting and tactics development. This paper proposes a ball event detection method to achieve high detection rate by solving challenges including: the great variety of event length, the large intra-class difference of one event and the influence caused by ball trajectories....
In order to filter tracks of ship targets for space-based maritime surveillance using electronic reconnaissance satellites, an extended Kalman filter (EKF) algorithm in geographic coordinates is proposed in this paper. Firstly, different methods of Dead reckoning (DR) are analysed in different coordinate systems. Then, the formula of EKF based on middle latitude sailing is derived. Finally, satellite-based...
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