scholarly journals Integrated Estimation/Guidance Law against Exoatmospheric Maneuvering Targets

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-19 ◽  
Author(s):  
Mao Su ◽  
Lei Liu ◽  
Yongji Wang
Keyword(s):  
Monte Carlo ◽  
Kalman Filter ◽  
Differential Game ◽  
Extended Kalman Filter ◽  
Unscented Kalman Filter ◽  
Three Dimensional ◽  
Guidance Law ◽  
Maneuvering Targets ◽  
Integrated Estimation ◽  
Guidance Problem

An integrated guidance integrated estimation/guidance law is designed for exoatmospheric interceptors equipped with divert thrusters and optical seekers to intercept maneuvering targets. This paper considers an angles-only guidance problem for exoatmospheric maneuvering targets. A bounded differential game-based guidance law is derived against maneuvering targets using zero-effort-miss (ZEM). Estimators based the extended Kalman filter (EKF) and the unscented Kalman filter (UKF) are designed to estimate LOS rates that are contaminated by noise and target maneuver. Furthermore, to improve the observability of the range, an observability enhancement differential game guidance law is derived. The guidance law and the estimator are integrated together in the guidance loop. The proposed integrated estimation/guidance law has been tested in several three-dimensional nonlinear interception scenarios. Numerical simulations on a set of Monte-Carlo simulations prove the validity and superiority of the proposed guidance law in hit-to-kill interception.

Pervasive underwater passive target tracking for the computation of standard deviation solution in a 3D environment

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
M. Kavitha Lakshmi ◽  
S. Koteswara Rao ◽  
Kodukula Subrahmanyam
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Kalman Filter ◽  
Standard Deviation ◽  
Target Tracking ◽  
Unscented Kalman Filter ◽  
Three Dimensional ◽  
Content Type ◽  
3D Space ◽  
Underwater Target

PurposeNowadays advancement in acoustic technology can be explored with marine assets. The purpose of the paper is pervasive computing underwater target tracking has aroused military and civilian interest as a key component of ocean exploration. While many pervasive techniques are currently found in the literature, there is little published research on the effectiveness of these paradigms in the target tracking context.Design/methodology/approachThe unscented Kalman filter (UKF) provides good results for bearing and elevation angles only tracking. Detailed methodology and mathematical modeling are carried out and used to analyze the performance of the filter based on the Monte Carlo simulation.FindingsDue to the intricacy of maritime surroundings, tracking underwater targets using acoustic signals, without knowing the range parameter is difficult. The intention is to find out the solution in terms of standard deviation in a three-dimensional (3D) space.Originality/valueA new method is found for the acceptance criteria for range, course, speed and pitch based on the standard deviation for bearing and elevation 3D target tracking using the unscented Kalman filter covariance matrix. In the Monte Carlo simulation, several scenarios are used and the results are shown.

Real-Time Signal Denoising Algorithm in Wheel Force Transducer

2014 ◽  
Vol 615 ◽  
pp. 244-247
Author(s):  
Dong Wang ◽  
Guo Yu Lin ◽  
Wei Gong Zhang
Keyword(s):  
Kalman Filter ◽  
Real Time ◽  
Extended Kalman Filter ◽  
Unscented Kalman Filter ◽  
Force Transducer ◽  
Time Signal ◽  
Signal Denoising ◽  
Observation Function ◽  
Simulation Results ◽  
Wheel Force Transducer

The wheel force transducer (WFT) is used to measure dynamic wheel loads. Unlike other force sensors, WFT is rotating with the wheel. For this reason, the outputs and the inputs of the transducer are nonlinearly related, and traditional Kalman Filter is not suitable. In this paper, a new real-time filter algorithm utilizing Quadrature Kalman Filter (QKF) is proposed to solve this problem. In Quadrature Kalman Filter, Singer model is introduced to track the wheel force, and the observation function is established for WFT. The simulation results illustrate that the new filter outperforms the traditional Unscented Kalman Filter (UKF) and Extended Kalman Filter (EKF).

scholarly journals Tracking of pendulum using particle filter with residual resampling

2018 ◽  
Vol 7 (2.7) ◽  
pp. 12
Author(s):  
Penumarty Hiranmayi ◽  
Kola Sai Gowtham ◽  
S Koteswara Rao ◽  
V Gopi Tilak
Keyword(s):  
Monte Carlo ◽  
Kalman Filter ◽  
Particle Filter ◽  
Extended Kalman Filter ◽  
Horizontal Direction ◽  
Bayesian Filtering ◽  
Discrete State ◽  
Harmonic Motion ◽  
Simple Pendulum ◽  
Importance Resampling

The phenomenon of simple harmonic motion is more vigilantly explained using a simple pendulum. The angular motion of a pendulum is linear in nature. But the analysis of the motion along the horizontal direction is non-linear. To estimate this, several algorithms like the Kalman filter, Extended Kalman Filter etc. are adopted. Here in this paper, Particle filter is chosen which is a method to form Monte Carlo approximations to the solutions of Bayesian filtering equations. Sequential importance resampling based Particle filters are used where the filtering distributions are multi-nodal or consist of discrete state components since under these circumstances the Bayesian approximations do not always work well.

scholarly journals Extraction and Filter Algorithm of Guidance Information for Full-strapdown Seeker on Rotation Missile

2018 ◽  
Vol 214 ◽  
pp. 03008 ◽  
Author(s):  
YongShan Liu ◽  
Li Song ◽  
JingLong Li
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Simple Structure ◽  
Unscented Kalman Filter ◽  
High Reliability ◽  
Engineering Application ◽  
Line Of Sight ◽  
Light Weight ◽  
Rate Information ◽  
Guidance Information

Strapdown seekers are superior to platform seekers for their simple structure, high reliability and light weight but cannot measure the line-of-sight angle rate information for the guidance of rotation missile directly. This paper aims at the engineering application of full-strapdown seekers on rotation missile problem. Firstly, a line-of-sight angle rate solution model is established. Based on the MATLAB, the extended Kalman filter (EKF) algorithm and unscented Kalman filter (UKF) algorithm are used to estimate the line-of-sight angle rate information of the full-strapdown seekers. The results show that using EKF filter and UKF filter both can obtain effective guidance information and the UKF’s effect is better.

scholarly journals A New Linear Regression Kalman Filter with Symmetric Samples

Symmetry ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2139
Author(s):  
Xiuqiong Chen ◽  
Jiayi Kang ◽  
Mina Teicher ◽  
Stephen S.-T. Yau
Keyword(s):  
Kalman Filter ◽  
Linear Regression ◽  
Particle Filter ◽  
Normal Distribution ◽  
Extended Kalman Filter ◽  
Nonlinear Filtering ◽  
Unscented Kalman Filter ◽  
Standard Normal Distribution ◽  
Leibler Divergence ◽  
Standard Normal

Nonlinear filtering is of great significance in industries. In this work, we develop a new linear regression Kalman filter for discrete nonlinear filtering problems. Under the framework of linear regression Kalman filter, the key step is minimizing the Kullback–Leibler divergence between standard normal distribution and its Dirac mixture approximation formed by symmetric samples so that we can obtain a set of samples which can capture the information of reference density. The samples representing the conditional densities evolve in a deterministic way, and therefore we need less samples compared with particle filter, as there is less variance in our method. The numerical results show that the new algorithm is more efficient compared with the widely used extended Kalman filter, unscented Kalman filter and particle filter.

scholarly journals Fault Diagnosis of PMSG Stator Inter-Turn Fault Using Extended Kalman Filter and Unscented Kalman Filter

Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2972 ◽  
Author(s):  
Waseem El Sayed ◽  
Mostafa Abd El Geliel ◽  
Ahmed Lotfy
Keyword(s):  
Kalman Filter ◽  
Fault Diagnosis ◽  
Extended Kalman Filter ◽  
Continuous Monitoring ◽  
Unscented Kalman Filter ◽  
Fault Tolerant ◽  
Synchronous Generator ◽  
Operating Conditions ◽  
Practical Implementation ◽  
Complete Failure

Since the permeant magnet synchronous generator (PMSG) has many applications in particular safety-critical applications, enhancing PMSG availability has become essential. An effective tool for enhancing PMSG availability and reliability is continuous monitoring and diagnosis of the machine. Therefore, designing a robust fault diagnosis (FD) and fault tolerant system (FTS) of PMSG is essential for such applications. This paper describes an FD method that monitors online stator winding partial inter-turn faults in PMSGs. The fault appears in the direct and quadrature (dq)-frame equations of the machine. The extended Kalman filter (EKF) and unscented Kalman filter (UKF) were used to detect the percentage and the place of the fault. The proposed techniques have been simulated for different fault scenarios using Matlab®/Simulink®. The results of the EKF estimation responses simulation were validated with the practical implementation results of tests that were performed with a prototype PMSG used in the Arab Academy For Science and Technology (AAST) machine lab. The results showed impressive responses with different operating conditions when exposed to different fault states to prevent the development of complete failure.

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