With social development and continual technological innovation, the optimal control model is widely used in various scientific fields daily life, becoming a basic tool for expression. Herein, an built, improved parameter cascading algorithm cycling iteration are combined to solve unknown parameters function of model. The model's accuracy was validated through numerical simulations. Then, substituted into bank credit loan source data validate results. This model, based on iteration, dynamic...

Spatial registration and track-to-track association (which are mutually coupled) essential parts in the process of multi-sensor information fusion. The quality spatial track algorithm directly influences subsequent fusion performance. Aiming to solve problem case where incomplete measurements provided by different sensors, this paper proposes a residual bias estimation (RBER) method based on maximum likelihood sequential m-best new target density (SMBTANTD). RBER realizes update filtering...

Spatial registration is a prerequisite for data fusion. Existing methods primarily focus on similar sensor scenarios and rely accurate association assumptions. To address the heterogeneous in complex scenarios, this paper proposes Gaussian mixture probability hypothesis density (GM-PHD)-based algorithm bias registration, accompanied by an adaptive measurement iterative update algorithm. Firstly, constructing augmented target state motion models, closed-form expression prediction derived...

As global demand for renewable energy and electric vehicles increases, the need lithium has surged significantly. Extracting from salt lake brine become a cutting-edge technology in resource production. In this study, two-dimensional (2D) GO/MXene composite membranes were fabricated using pressure-assisted filtration with polyethyleneimine (PEI) coating, resulting positively charged PEI-GO/MXene membranes. These innovative membranes, taking advantage of synergistic effects interlayer channel...

Knowledge of the clutter rate is critical importance in multi-target Bayesian tracking. However, estimating a difficult problem practice. In this paper, an improved multi-Bernoulli filter based on random finite sets for tracking accommodating non-linear dynamic and measurement models, as well unknown rate, proposed radar sensors. The incorporates amplitude information into state spaces to improve discrimination between actual targets clutters, while adaptively generating new-born object...

News reporting events without peoplepsilas review is usually very short, so vector space model (VSM) used for representing long text-based documents not suitable describing news. In addition, VSM can represent basic questions in news: who, what, when, where. A new kind of text needed to manipulate this paper, a news ontology incorporating some metadata OpenCyc,EventsML-G2, NewsML-G2, and industry format (NITF) designed at first. What more important that relations domain are also described...

A deinterleaving algorithm of radar signal based on DSP is presented in this paper, which according to the structure system, characteristics PDW (pulse descriptor word) and histogram method. The threshold determination, accumulation PRI repetition interval) others applied different fields are introduced detail. experimental results comparison with transform method show that paper does not only achieve excellent performance mixed normal pulses, staggered pulses jittered high density 200...

Traditional multi-target tracking algorithms assume that each target can generate at most one detection per scan. However, a may produce multiple detections (MDs) in many practical applications, e.g. over-the-horizon radar (OTHR), for extended and with sensors. In this study, the authors propose new algorithm targets MD observation. The proposed technique is based on labelled random finite set (RFS), which estimates number of trajectories their states. Furthermore, they two methods,...

Multi-target tracking is an extremely challenging task when targets move in the formation of groups and interact with each other. Group target has to deal this problem contrast independently moving as assumed most multi-target algorithms. A feasible approach for group estimate structure modify motion model prediction step tracker according structure. In paper, we propose ad hoc labeled multi-Bernoulli (LMB) filter interaction, which use stochastic differential equation joint by using graph...

Conventional Multi-Bernoulli (MBer) filter assumes that the birth MBer Random finite set (RFS) is known a priori. However, this not true for practical scenario. This paper proposes novel extension of which eliminates reliance prior RFS and relaxes limitation in new-born target appearance volume. The proposed classifies measurements into survival measurements, adaptively generates using measurements. filtering equations distinguish persistent targets are derived. A Sequential Monte-Carlo...

To realize multitarget trajectory tracking under non-Gaussian heavy-tailed noise, we propose a Gaussian–Student t-mixture distribution-based cardinality probability hypothesis density filter (GSTM-TCPHD). We introduce the multi-sensor GSTM-TCPHD (MS-GSTM-TCPHD) to enhance performance. Conventional (CPHD) filters typically assume Gaussian noise and struggle accurately establish target trajectories when faced with distributions. Heavy-tailed leads significant estimation errors dispersion....

Nowadays, it is still a great challenge to detect and locate indoor humans using frequency-modulated continuous-wave radar accurately. Due the interference of environment complex objects such as green plants, signal may penetrate, reflect, refract, scatter, echo signals will contain noise, clutter, multipath different characteristics. Therefore, method combined with comprehensive non-target removal human localization proposed achieve position estimation target. Time-variant clutter...

Traditional multitarget tracking algorithms assume that each target can generate at most one detection per scan. However, in the over-the-horizon radar (OTHR), a may produce multiple detections because of multipath propagation. In this paper, we propose new algorithm, called generalized labeled multi-Bernoulli (MP-GLMB) filter, to effectively track targets such multiple-detection systems. The proposed technique is based on random finite set (RFS), which estimates number and trajectories...

In ground tracking applications, the majority of targets are vehicles, which moving on roads. Since road maps can be achieved easily, track performance and continuity enhanced by exploiting map information. this paper, we adopt a one-dimensional coordinates motion model use linear segments to approximate curved road. Incorporating modeled information, probability hypothesis density (PHD) multiple target filter is applied estimate these constrained targets. We Gaussian Mixture (GM) variant...

Aiming at the problem of radar sensor registration on a mobile platform, this study uses multiple radars to estimate biases under earth-centred earth-fixed coordinate system, which provides more accurate information for data fusion. Compared maximum likelihood (MLR) algorithm, can only offset biases, novel extended MLR (EMLR) algorithm is proposed. The could radar-offset attitude and target real location simultaneously. simulation results verified that EMLR effectively improve precision registration.

This study introduces a special converted measurement Kalman filter (CMKF) algorithm which apply to satellite for tracking target. Typical CMKF applies radar measures targets in spherical coordinate system. The new can be used by target's latitude and longitude. Improved tracks target simple situation but is not able deal with multi-target information missing situation. Multiple hypothesis (MHT) track accurately has the ability initial end at all times. For satellite, MHT use improved...

Group tracking based on Markov Chain Monte Carlo particle filter (MCMC-PF) algorithm has high accuracy of individual target and group tracking, but the main problem MCMC-PF is calculation burden, that's because it considers all kinds hypotheses between state vector measurement in observation model. Therefore, this paper, we originally use results data association as a prior to do management, which will reduce variety feasible hypotheses. We also raise new method for proposal information...