The Fast Diagonal-Matrix-Weight IMM Algorithm for Target Tracking

2012 ◽  
Vol 461 ◽  
pp. 132-137
Author(s):  
Yang Fu ◽  
Ming Wei ◽  
Hai Chuan Zhang ◽  
Liang Gao
Keyword(s):  
Stochastic Process ◽  
Computational Complexity ◽  
Target Tracking ◽  
Real Time ◽  
Probability Density Functions ◽  
Diagonal Matrix ◽  
Estimation Accuracy ◽  
Density Functions ◽  
Alternative Algorithm ◽  
Real Time Application

The diagonal-matrix-weight IMM (DIMM) algorithm can solve the IMM algorithm confusions of probability density functions (PDFs) and probability masses of stochastic process. Combingandfilter，the Fast-IMM algorithm has a better performance both in accuracy and reducing computational complexity. In order to improve the estimation accuracy and computational complexity，we apply Fast-IMM method to DIMM algorithm. Therefore，A new method, Fast diagonal-matrix-weight IMM (fast-DIMM) algorithm, is proposed in this paper to heighten the real-time application of DIMM algorithm. Simulations indicate that the proposed fast-DIMM algorithm is a competitive alternative algorithm to the IMM algorithm in real time application

An Improvement of the Rapidly-Exploring Random Tree Method for Path Planning of a Car-Like Robot in Virtual Environment

2015 ◽  
Vol 772 ◽  
pp. 471-476 ◽  
Author(s):  
Teodora Gîrbacia ◽  
Gheorghe Mogan
Keyword(s):  
Computational Complexity ◽  
Path Planning ◽  
Real Time ◽  
Virtual Environment ◽  
Minimum Distance ◽  
Optimal Path ◽  
Random Tree ◽  
Real Time Application ◽  
Simulation Time ◽  
Tree Method

In this paper we present a method of reducing the computational complexity necessary in path planning for a car-like robot in order to generate the optimal path according to the constrains set by the user. The proposed method implies adding the following constrains: setting the maximum and minimum distance between the possible paths and the obstacles placed in the virtual environment in order to reduce the simulation time and to obtain a real-time application and to remove the paths that contain unnecessary turns around the environment without avoiding an obstacle. By applying this method the simulation complexity is reduced and the optimal path is easier to find.

scholarly journals An Efficient Near-Field Localization Method of Coherently Distributed Strictly Non-circular Signals

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5176
Author(s):  
Meidong Kuang ◽  
Ling Wang ◽  
Yuexian Wang ◽  
Jian Xie
Keyword(s):  
Near Field ◽  
Integral Form ◽  
Approximate Expression ◽  
Probability Density Functions ◽  
Estimation Accuracy ◽  
Density Functions ◽  
Classical Probability ◽  
One Dimensional ◽  
Spatially Distributed ◽  
Field Localization

For the near-field localization of non-circular distributed signals with spacial probability density functions (PDF), a novel algorithm is proposed in this paper. The traditional algorithms dealing with the distributed source are only for the far-field sources, and they need two-dimensional (2D) search or omit the angular spread parameter. As a result, these algorithms are no longer inapplicable for near-filed localization. Hence the near-filed sources that obey a classical probability distribution are studied and the corresponding specific expressions are given, providing merits for the near-field signal localization. Additionally, non-circularity of the incident signal is taken into account in order to improve the estimation accuracy. For the steering vector of spatially distributed signals, we first give an approximate expression in a non-integral form, and it provides the possibility of separating the parameters to be estimated from the spatially discrete parameters of the signal. Next, based on the rank-reduced (RARE) algorithm, direction of arrival (DOA) and range can be obtained through two one-dimensional (1-D) searches separately, and thus the computational complexity of the proposed algorithm is reduced significantly, and improvements to estimation accuracy and identifiability are achieved, compared with other existing algorithms. Finally, the effectiveness of the algorithm is verified by simulation.

A Novel Divided Differential Filter with Application to Target Tracking

2014 ◽  
Vol 644-650 ◽  
pp. 2510-2513
Author(s):  
Yu Zhe Wang ◽  
Juan Wang ◽  
Hang Su ◽  
Min Wang
Keyword(s):  
Target Tracking ◽  
Real Time ◽  
Newton Iteration ◽  
Estimation Accuracy ◽  
Tracking Problem ◽  
Computation Load ◽  
Terminal Guidance ◽  
Guidance Model

In order to meet the requirements of target tracking problem in terminal guidance of intercepting an aircraft, based on Gaussian-Newton Iteration strategy, a novel divided differential filter was introduced, which guaranteed higher estimation accuracy than the commonly used EKF and UKF methods. The relative small computation load made it possible for real time implantation of the filter and simulations based on a typical terminal guidance model proved the correctness and effectiveness of the proposed filter.

scholarly journals A Fast Signal Estimation Method Based on Probability Density Functions for Fault Feature Extraction of Rolling Bearings

2019 ◽  
Vol 9 (18) ◽  
pp. 3768
Author(s):  
Shijun Li ◽  
Weiguo Huang ◽  
Juanjuan Shi ◽  
Xingxing Jiang ◽  
Zhongkui Zhu
Keyword(s):  
Feature Extraction ◽  
Fault Diagnosis ◽  
Computational Complexity ◽  
Probability Density Functions ◽  
Density Functions ◽  
Rolling Bearings ◽  
Vibration Signals ◽  
Transient Component ◽  
Fast Estimation ◽  
Fault Feature Extraction

Fault diagnosis of rolling bearings is essential to ensure the efficient and safe operation of mechanical equipment. The extraction of fault features of the repetitive transient component from noisy vibration signals is key to bearing fault diagnosis. However, the bearing fault-induced transients are often submerged by strong background noise and interference. To effectively detect such fault-related transient components, this paper proposes a probability- and statistics-based method. The maximum-a-posteriori (MAP) estimator combined with probability density functions (pdfs) of the repetitive transient component, which is modeled by a mixture of two Laplace pdfs and noise, were used to derive the fast estimation model of the transient component. Subsequently, the LapGauss pdf was adopted to model the noisy coefficients. The parameters of the model derived could then be estimated quickly using the iterative expectation–maximization (EM) algorithm. The main contributions of the proposed statistic-based method are that: (1) transients and their wavelet coefficients are modeled as mixed Laplace pdfs; (2) LapGauss pdf is used to model noisy signals and their wavelet coefficients, facilitating the computation of the proposed method; and (3) computational complexity changes linearly with the size of the dataset and thus contributing to the fast estimation, indicated by analysis of the computational performance of the proposed method. The simulation and experimental vibration signals of faulty bearings were applied to test the effectiveness of the proposed method for fast fault feature extraction. Comparisons of computational complexity between the proposed method and other transient extraction methods were also conducted, showing that the computational complexity of the proposed method is proportional to the size of the dataset, leading to a high computational efficiency.

Spatial Interpolators for Intra-Frame Resampling of SAR Videos: A Comparative Study Using Real-Time HD, Medical and Radar Data

2020 ◽  
Vol 15 (2) ◽  
pp. 144-196 ◽  
Author(s):  
Mohammad R. Khosravi ◽  
Sadegh Samadi ◽  
Reza Mohseni
Keyword(s):  
Computational Complexity ◽  
Real Time ◽  
Video Compression ◽  
Nearest Neighbor ◽  
Radar Data ◽  
Edge Preservation ◽  
Edge Information ◽  
Video Codecs ◽  
Comparative Results ◽  
Interesting Area

Background: Real-time video coding is a very interesting area of research with extensive applications into remote sensing and medical imaging. Many research works and multimedia standards for this purpose have been developed. Some processing ideas in the area are focused on second-step (additional) compression of videos coded by existing standards like MPEG 4.14. Materials and Methods: In this article, an evaluation of some techniques with different complexity orders for video compression problem is performed. All compared techniques are based on interpolation algorithms in spatial domain. In details, the acquired data is according to four different interpolators in terms of computational complexity including fixed weights quartered interpolation (FWQI) technique, Nearest Neighbor (NN), Bi-Linear (BL) and Cubic Cnvolution (CC) interpolators. They are used for the compression of some HD color videos in real-time applications, real frames of video synthetic aperture radar (video SAR or ViSAR) and a high resolution medical sample. Results: Comparative results are also described for three different metrics including two reference- based Quality Assessment (QA) measures and an edge preservation factor to achieve a general perception of various dimensions of the mentioned problem. Conclusion: Comparisons show that there is a decidable trade-off among video codecs in terms of more similarity to a reference, preserving high frequency edge information and having low computational complexity.

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