The unrestricted development and utilization of marine resources have resulted in a series practical problems, such as the destruction ecology. wide application radar, satellites other detection equipment has gradually led to large variety large-capacity spatiotemporal trajectory data from vast number sources. In field domain awareness, there is an urgent need use relevant information technology means control monitor ships accurately classify identify ship behavior patterns through...

A new subspace method is proposed to solve the bearing-only target localization (BOTL) problem. Instead of linearizing nonlinear bearing equations form least-squares optimization, we construct a scalar product matrix by making full use all and intersensor geometric information. After exploiting dimension eigenstructure matrix, devise algorithm for BOTL with its weights computed from prior location estimate. Simulation results show that achieves mean square error performance close Cramér-Rao...

One open issue of target detection for synthetic aperture radar (SAR) images is the capture effect from clutter edge and interfering outliers, including surrounding targets in multitarget environment, sidelobes, ghosts. To address this issue, a superpixel-level constant false-alarm rate (CFAR) detector proposed based on truncated Gamma statistics multilook intensity SAR data. Superpixel segmentation serves as preprocessing procedure to divide image into meaningful patches. By automatic...

Attention mechanisms have demonstrated great potential in improving the performance of deep convolutional neural networks (CNNs). However, many existing methods dedicate to developing channel or spatial attention modules for CNNs with lots parameters, and complex inevitably affect CNNs. During our experiments embedding Convolutional Block Module (CBAM) light-weight model YOLOv5s, CBAM does influence speed increase complexity while reduce average precision, but Squeeze-and-Excitation (SE) has...

The constant false alarm rate (CFAR) detectors are well studied for ship detection in SAR images, which suffer performance degradation due to the capture effect from interfering outliers, such as nearby targets, sidelobes and ghosts multi-target environments. To address this issue, clutter truncation scheme is adopted reduce outlier contamination samples that accuracy of modeling can be improved. However, selection depth difficult, often resorts sensitivity study. In paper, complex signal...

This paper addresses the issue of reference signal being contaminated by target echoes due to factors such as wide beamwidths, beam pointing errors, or site errors in passive bistatic radar (PBR). Such contamination can lead impurity and subsequently degrade performance traditional object detection methods. To overcome this challenge, a novel method centered around signal’s purification is presented. The proposed involves modeling, analysis, localization, impure signal. First, new model...

In distributed information fusion application, developing an efficient track-to-track association approach becomes crucially important which may significantly benefit the sequent procedure. This paper proposes a novel method specialized for multitarget tracking using more than two sensors. order to mathematically interpret how probable that tracks from different sensors are same targets, fuzzy membership of calculated, whose value is between 0 and 1, with bigger values indicating higher...

Semi-supervised learning has been proven to be effective in utilizing unlabeled samples mitigate the problem of limited labeled data. Traditional semi-supervised methods generate pseudo-labels for and train classifier using both pseudo-labeled samples. However, data-scarce scenarios, reliance on initial generation can degrade performance. Methods based consistency regularization have shown promising results by encouraging consistent outputs different semantic variations same sample obtained...

A localization and tracking algorithm for an early-warning system based on the information fusion of Infrared (IR) sensor Laser Detection Ranging (LADAR) is proposed. The proposed Kalman filter scheme incorporates Out-of-Sequence Measurements (OOSMs) to address long-range, high-speed incoming targets be tracked by networked Remote Observation Sites (ROS) in cluttered environments. Rauch⁻Tung⁻Striebel (RTS) fixed lag smoothing employed technique further improve accuracy, which, turn, used...

Motion characterization, including Doppler and micro-Doppler, is crucial for the detection identification of high-speed underwater targets. Under high-frequency short-range conditions, targets cannot be simply regarded as single highlight they exhibit a complex structure with multiple scattering centers accompanied by distinct micro-motions. To address this multi-highlight multi-micro-motion scenario, model proposed to characterize motion features Firstly, mathematical established represent...

The theory of fuzzy sets has been used to deal with image enhancement problems some degraded images in which there are uncertainties and inaccuracies. For those kinds images, good effect can be obtained using a sets-based method instead the traditional approaches. A generalized algorithm is proposed based on algorithm. This new retains advantages gray level transformation, therefore suitable for handling that have less levels low contrast. Finally, simulated example given demonstrate...

In practical operation, the system parameters of a permanent magnet linear motor are affected by unknown factors, including nonlinear friction, sudden load changes, thrust fluctuations, and so on. Therefore, controller designed for fixed often cannot produce satisfactory results. To solve this problem, novel design method systems based on backstepping is proposed in article. The control scheme does not require values or range changes advance but constructs an update law to perform online...

The modeling of channel and temporal information is crucial importance for action recognition tasks. To build a high-performance network by effectively capturing information, we propose CLS-Net: an algorithm based on channel-temporal modeling. proposed CLS-Net characterizes inserting multiple modules to end-to-end backbone network, including attention module (CA module) long-term (LT short-term (ST information. Specifically, the CA extracts correlation between feature channels so can learn...

In traditional Chinese medical (TCM) science, tongue images can be observed for diagnosis; however, the diagnosis of TCM is influenced by subjective factors doctors, and results vary from person to person. Quantitative improve accuracy increase application value. this paper, digital image processing pattern recognition technologies are employed on mobile device classify collected in different health states. First, through grayscale integral projection processing, trough found localize body....

The variable structure multiple-model (VSMM) estimation approach, one of the (MM) approaches, is popular in handling state problems with mode uncertainties. In VSMM algorithms, model sequence set adaptation (MSA) plays a key role. MSA methods are challenged both theory and practice for target modes real observation error distributions usually uncertain practice. this paper, geometrical entropy (GE) measure proposed so that achieved on minimum (MGE) principle. Consequently, (MGEMM) framework...