scholarly journals Adaptive Tracking Method of Distorted Voltage Using IMM Algorithm under Grid Frequency Fluctuation Conditions

Energies ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 7944
Author(s):  
Haoyao Nie ◽  
Xiaohua Nie
Keyword(s):  
Tracking Error ◽  
Sine Wave ◽  
Set Covering ◽  
Frequency Fluctuation ◽  
Detection Accuracy ◽  
Multiple Model ◽  
Fixed Frequency ◽  
Frequency Detection ◽  
Interactive Multiple Model ◽  
Tracking Model

This paper newly proposes an interactive multiple model (IMM) algorithm to adaptively track distorted AC voltage with the grid frequency fluctuation. The usual tracking methods are Kalman filter (KF) algorithm with a fixed frequency and KF algorithm with frequency identifier. The KF algorithm with a fixed frequency has a larger covariance parameter to guarantee the tracking robustness. However, it has a large tracking error. The KF algorithm with frequency identifier overly depends on the accuracy and stability of frequency identifier. The advantage of the proposed method is that it is decoupled from frequency detection and does not depend on frequency detection accuracy. First, the orthogonal vector dynamic (OVD) tracking model of the sine wave is established. Then, a model set covering the grid frequency fluctuation range is formed, and a new OVD-IMM tracking algorithm is proposed in combination with IMM algorithm. In the end, the effectiveness and accuracy of the proposed OVD-IMM algorithm are verified through simulations and experiments.

scholarly journals Application of Interactive Multiple Model Adaptive Five-Degree Cubature Kalman Algorithm Based on Fuzzy Logic in Target Tracking

Symmetry ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 767
Author(s):  
Jian Wan ◽  
Peiwen Ren ◽  
Qiang Guo
Keyword(s):  
Fuzzy Logic ◽  
Simulation Analysis ◽  
Model Simulation ◽  
Multiple Model ◽  
Fuzzy Logic Algorithm ◽  
Error Covariance ◽  
Speed Tracking ◽  
Model Probability ◽  
Interactive Multiple Model ◽  
Tracking Model

Aiming at the shortcomings of low precision, hysteresis, and poor robustness of the general interactive multimodel algorithm in the “snake-like” maneuver tracking of anti-ship missiles, an interactive multimodel adaptive five-degree cubature Kalman algorithm based on fuzzy logic (FLIMM5ACKF) is proposed. The algorithm mainly includes adaptive five-degree cubature Kalman algorithm (A5CKF) and fuzzy logic algorithm (FL). A5CKF uses the Sage–Husa noise estimation principle to propose a state error covariance adaptive five-degree cubature Kalman algorithm to improve the performance of state estimation. Then, the fuzzy logic algorithm (FL) is added to the model probability update module to control the model probability update module. Finally, by setting the same tracking model simulation analysis, the algorithm has better convergence speed, tracking effect and robustness than the interactive multimodel cubature Kalman algorithm (IMMCKF), the interactive multimodel five-degree cubature Kalman algorithm (IMM5CKF) and the interactive multimodel adaptive five-degree cubature Kalman (IMMA5CKF).

scholarly journals An approach of constant false alarm ratio for improved target tracking

2020 ◽  
Vol 70 (3) ◽  
pp. 17-23
Author(s):  
Zvonko Radosavljević ◽  
Dejan Ivković
Keyword(s):  
False Alarm ◽  
Tracking Error ◽  
Probability Of Detection ◽  
Interacting Multiple Model ◽  
Multiple Model ◽  
Moving Targets ◽  
False Alarm Ratio ◽  
Motion Models ◽  
Areas Of Interest

Each radar has the function of surveillance of certain areas of interest. In particular, the radar also has the function of tracking moving targets in that territory with some probability of detection, which depends on the type of detector. Constant false alarm ratio (CFAR) is a very commonly used detector. Changing the probability of target detection can directly affect the quality of tracking the moving targets. The paper presents the theoretical basis of the influence of CFAR detectors on the quality of tracking, as well as an approach to the selection of CFAR detectors, CATM CFAR, which enables better monitoring by the Interacting Multiple Model (IMM) algorithm with two motion models. Comparative analysis of CA and CATM algorithm realized by numerical simulations has shown that CATM CFAR gives less tracking error with proportionally the same computer resources.

scholarly journals Demodulation Technique Based on Laser Interference for Weak Photo-Acoustic Signals on Water Surface

2018 ◽  
Vol 8 (12) ◽  
pp. 2423 ◽  
Author(s):  
Xiaolin Zhang ◽  
Hongjie Mao ◽  
Wenyan Tang
Keyword(s):  
Acoustic Wave ◽  
Surface Acoustic Wave ◽  
High Frequency ◽  
Water Surface ◽  
Processing System ◽  
Detection Accuracy ◽  
Laser Interference ◽  
Characteristic Ratio ◽  
Frequency Detection ◽  
Interference Signals

To detect underwater sound-generating targets, a water surface acoustic wave laser interference and signal demodulation technique is proposed in this paper. The underlying principle of this technique involves casting a laser beam onto the water surface disturbed by an underwater acoustic source and creating interference between lights reflected by the surface and reference lights. A data acquisition and processing system was employed to obtain water surface acoustic wave information from the interference signals by means of demodulation, thus allowing detection of the underwater target. For the purpose of this study, an interference detection platform was set up in an optical dark chamber. High-frequency water surface fluctuations were introduced in the reference optical path as the phase generated carriers to create laser interference signals in two different paths, which received demodulation based on an improved arc tangent demodulation algorithm and characteristic ratio algorithm, respectively, in view of their different frequencies. Water surface wave information was then derived from such low-frequency and high-frequency signals. According to test results, in the frequency range of 200 Hz–10 kHz, the frequency detection accuracy was better than 1 Hz. The amplitude measurements exhibited high repeatability, with a standard deviation lower than 2.5 nm. The theory proposed in this paper is therefore experimentally verified with good results.

scholarly journals Assessment of Cognitive Aging Using an SSVEP-Based Brain–Computer Interface System

2019 ◽  
Vol 3 (2) ◽  
pp. 29 ◽  
Author(s):  
Saraswati Sridhar ◽  
Vidya Manian
Keyword(s):  
Cognitive Decline ◽  
Cognitive Aging ◽  
Age Groups ◽  
Detection Accuracy ◽  
Cognitive Deterioration ◽  
Age Group ◽  
Frequency Detection ◽  
Band Power ◽  
Age Related ◽  
Bci System

Cognitive deterioration caused by illness or aging often occurs before symptoms arise, and its timely diagnosis is crucial to reducing its medical, personal, and societal impacts. Brain–computer interfaces (BCIs) stimulate and analyze key cerebral rhythms, enabling reliable cognitive assessment that can accelerate diagnosis. The BCI system presented analyzes steady-state visually evoked potentials (SSVEPs) elicited in subjects of varying age to detect cognitive aging, predict its magnitude, and identify its relationship with SSVEP features (band power and frequency detection accuracy), which were hypothesized to indicate cognitive decline due to aging. The BCI system was tested with subjects of varying age to assess its ability to detect aging-induced cognitive deterioration. Rectangular stimuli flickering at theta, alpha, and beta frequencies were presented to subjects, and frontal and occipital Electroencephalographic (EEG) responses were recorded. These were processed to calculate detection accuracy for each subject and calculate SSVEP band power. A neural network was trained using the features to predict cognitive age. The results showed potential cognitive deterioration through age-related variations in SSVEP features. Frequency detection accuracy declined after age group 20–40, and band power declined throughout all age groups. SSVEPs generated at theta and alpha frequencies, especially 7.5 Hz, were the best indicators of cognitive deterioration. Here, frequency detection accuracy consistently declined after age group 20–40 from an average of 96.64% to 69.23%. The presented system can be used as an effective diagnosis tool for age-related cognitive decline.

scholarly journals TRANSPORT OF RESUSPENDED DREDGED SEDIMENT NEAR CORAL REEFS AT APRA HARBOR, GUAM

2012 ◽  
Vol 1 (33) ◽  
pp. 99
Author(s):  
Tahirih Lackey ◽  
Joseph Gailani ◽  
Sung-Chan Kim ◽  
David King ◽  
Deborah Shafer
Keyword(s):  
Coral Reef ◽  
Coral Reefs ◽  
Model Simulation ◽  
Selection Process ◽  
A Priori ◽  
Sediment Concentration ◽  
Exposure Level ◽  
Multiple Model ◽  
Model Studies ◽  
Tracking Model

Model studies have been conducted to investigate the potential coral reef exposure from proposed dredging associated with development of a new deepwater wharf in outer Apra Harbor, Guam. The Particle Tracking Model (PTM) was applied to quantify the exposure of coral reefs to material suspended by the dredging operations at proposed sites. Key PTM features include the flexible capability of continuous multiple releases of sediment parcels, control of parcel/substrate interaction, and the ability to track vast numbers of parcels efficiently. This flexibility has allowed for model simulation of the combined effects of sediment release from clamshell dredging, of chiseling to fracture limestone blocks, of silt curtains, and of flocculation. Because the rate of material released into the water column by some of the processes is not well understood or a priori known, the modeling protocol was to bracket parameters within reasonable ranges to produce a suite of potential results from multiple model runs. Data analysis results include mapping the time histories and the maximum values of suspended sediment concentration and deposition rate. Following exposure modeling, the next phase of the analysis has been an ecological assessment to translate the PTM exposure level predictions into predicted amounts of coral reef damage. The level of potential coral reef impact will be an important component of the final selection process for the new deepwater berthing site.

scholarly journals Improved Interacting Multiple Model Particle Filter Algorithm

2018 ◽  
Vol 36 (1) ◽  
pp. 169-175 ◽  
Author(s):  
Qiaoran Liu ◽  
Xun Yang
Keyword(s):  
Kalman Filter ◽  
Particle Filter ◽  
Target Tracking ◽  
Unscented Kalman Filter ◽  
Multiple Model ◽  
Tracking Accuracy ◽  
Proposal Distribution ◽  
Model Particle ◽  
Interactive Multiple Model ◽  
Particle Filter Algorithm

For the issue of limited filtering accuracy of interactive multiple model particle filter algorithm caused by the resampling particles don't contain the latest observation information, we made improvements on interactive multiple model particle filter algorithm in this paper based on mixed kalman particle filter algorithm. Interactive multiple model particle filter algorithm is proposed. In addition, the composed methods influence to tracking accuracy are discussed. In the new algorithm the system state estimation is generated with unscented kalman filter (UKF) first and then use the extended kalman filter (EKF) to get the proposal distribution of the particles, taking advantage of the measure information to update the particles' state. We compare and analyze the target tracking performance of the proposed algorithm of IMM-MKPF in this paper, IMM-UPF and IMM-EPF through the simulation experiment. The results show that the tracking accuracy of the proposed algorithm is superior to other two algorithms. Thus, the new method in this paper is effective. The method is of important to improve tracking accuracy further for maneuvering target tracking under the non-linear and non-Gaussian circumstances.

Sign in / Sign up

Export Citation Format

Share Document