• 제목/요약/키워드: improved Kalman filter algorithm

검색결과 77건 처리시간 0.025초

Research on detecting moving targets with an improved Kalman filter algorithm

  • Jia quan Zhou;Wei Wei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권9호
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    • pp.2348-2360
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    • 2023
  • As science and technology evolve, object detection of moving objects has been widely used in the context of machine learning and artificial intelligence. Traditional moving object detection algorithms, however, are characterized by relatively poor real-time performance and low accuracy in detecting moving objects. To tackle this issue, this manuscript proposes a modified Kalman filter algorithm, which aims to expand the equations of the system with the Taylor series first, ignoring the higher order terms of the second order and above, when the nonlinear system is close to the linear form, then it uses standard Kalman filter algorithms to measure the situation of the system. which can not only detect moving objects accurately but also has better real-time performance and can be employed to predict the trajectory of moving objects. Meanwhile, the accuracy and real-time performance of the algorithm were experimentally verified.

Kalman filter를 이용한 위치추정 알고리즘의 성능 분석 (Performance Analysis of Emitter Localization Using Kalman Filter)

  • 이준호;조성우;이동근
    • 한국군사과학기술학회지
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    • 제12권6호
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    • pp.727-732
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    • 2009
  • In this paper, the dependence of the Kalman filter-based emitter location algorithm on the initial estimate is investigated. Given all the LOB data, the initial estimate of the emitter location is obtained from the linear LSE algorithm with the former LOB data. Using the initial estimate, the Kalman filter algorithm is applied with the remaining LOB data to update the initial estimate. It is shown that as the number of data used in the calculation of the initial estimate increases, the accuracy of the final estimate is improved and the total computational complexity of obtaining the initial estimate and the final estimate increases. In addition, the dependence of the performance of the Kalman filter algorithm on the predefined constant is illustrated.

EM 알고리즘을 통한 칼만 필터의 성능 개선 (Improved Kalman filter performance via EM algorithm)

  • 강지혜;김성수
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2003년도 하계학술대회 논문집 D
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    • pp.2615-2617
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    • 2003
  • The Kalman filter is a recursive Linear Estimator for the linear dynamic systems(LDS) affected by two different noises called process noise and measurement noise both of which are uncorrelated white. The Expectation Maximization(EM) algorithm is employed in this paper as a preprocessor to reinforce the effectiveness of Kalman estimator. Particularly, we focus on the relation between Kalman filter and EM algorithm in the LDS. In this paper, we propose a new algorithm to improve the performance on the parameter estimation via EM algorithm, which improves the overall process of Kalman filtering. Since Kalman filter algorithm not only needs the system parameters but also is very sensitive the initial state conditions, the initial conditions decided through EM turns out to be very effective. In experiments, the computer simulation results ate provided to demonstrate the superiority of the proposed algorithm.

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Localization of Mobile Users with the Improved Kalman Filter Algorithm using Smart Traffic Lights in Self-driving Environments

  • Jung, Ju-Ho;Song, Jung-Eun;Ahn, Jun-Ho
    • 한국컴퓨터정보학회논문지
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    • 제24권5호
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    • pp.67-72
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    • 2019
  • The self-driving cars identify appropriate navigation paths and obstacles to arrive at their destinations without human control. The autonomous cars are capable of sensing driving environments to improve driver and pedestrian safety by sharing with neighbor traffic infrastructure. In this paper, we have focused on pedestrian protection and have designed an improved localization algorithm to track mobile users on roads by interacting with smart traffic lights in vehicle environments. We developed smart traffic lights with the RSSI sensor and built the proposed method by improving the Kalman filter algorithm to localize mobile users accurately. We successfully evaluated the proposed algorithm to improve the mobile user localization with deployed five smart traffic lights.

칼만 필터를 이용한 개선된 PID 제어기 설계 (The Design of an Improved PID Controller by Using the Kalman Filter)

  • 차인혁;권태종;한창수
    • 대한기계학회논문집A
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    • 제24권1호
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    • pp.7-15
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    • 2000
  • This paper suggests an auto-tuning I'll) control algorithm that uses the advantage of PID controller and improves the system performance. The PID gains being designed by th- conventional method are tuned through the plant parameter estimation. The Extended Kalman Filter is used for the estimation. It works as an observer and noise filter. Moreover, as the plant state and the uncertain parameter could be estimated simultaneously, the proposed algorithm is very useful in the tracking control of a system with uncertain parameter. The auto-tuning I'll) controller could maintain the system performance in the case that the plant parameters are uncertain or varying. The proposed control algorithm requires a correct estimation of the plant parameter. The controller stability and the performance is considered through the stability criteria and a servo motor model. The Kalman filter estimates the most sensitive plant parameter, which is determined by the sensitivity analysis.

국내 환경에 적합한 Kalman-filter 기반 사용자 운동거리 측정 알고리즘 설계 및 구현 (Design and Implementation of Kalman-filter Based User Movement Distance Algorithm Suitable for Domestic Environment)

  • 장영환;임수봉;박석천;이봉규;이상순
    • 한국정보통신학회논문지
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    • 제23권12호
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    • pp.1624-1630
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    • 2019
  • 세계적으로 스마트 디바이스 보급률이 증가하면서 운동 체크 등과 관련된 서비스들이 주목받고 있다. 그러나 기존 운동량 측정 서비스의 경우 고도 정보를 사용하지 않거나, GPS 고도 오차를 보정하지 않은 알고리즘을 사용하기 때문에 제공되는 운동거리 등이 정확하지 않다는 문제점이 있다. 따라서 본 논문에서는 기존의 문제점을 개선하기 위해 Kalman-filter를 기반으로 GPS와 기압고도계 센서 융합 알고리즘을 통해 고도 값 정확도 향상 및 좌표평면 사이거리 계산을 통해 Kalman-filter 기반 사용자 운동거리 측정 알고리즘을 설계 및 구현하였다. 설계한 알고리즘을 기존 알고리즘들과 비교한 결과, 기존 알고리즘에 비해 평균 약 2.17%의 정확도가 향상된 것을 확인하였다.

개선된 GPS 항법 알고리듬의 실시간 처리 주행 실험결과 (Field Test Results of the Improved GPS Navigation Algorithm)

  • 원종훈;고선준;이자성
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1998년도 하계학술대회 논문집 B
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    • pp.477-479
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    • 1998
  • This paper presents the results of the field of an improved GPS navigation algorithm. The improved GPS navigation algorithm is a modified Kalman filter which is designed to be ideally suited to car navigation in urban area where lack of GPS visibility is the major problem because of the frequent blockage of the GPS signals by tall buildings and other structures. The method allows the user to estimate its position when the number of visible GPS satellites becomes less than four by using altitude fixing and clock bias estimation techniques. The two estimation techniques are integrated with the Kalman filter in a mutually compensating manner and it is shown that the 3-dimensional position accuracy is well maintained when the number of the visible satellites drops down to two for a reasonable period of time. The post processing results are included to show the improved performance of the modified algorithm over a normal conventional GPS Kalman filter.

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CAMshift 기법과 칼만 필터를 결합한 객체 추적 시스템 (Object-Tracking System Using Combination of CAMshift and Kalman filter Algorithm)

  • 김대영;박재완;이칠우
    • 한국멀티미디어학회논문지
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    • 제16권5호
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    • pp.619-628
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    • 2013
  • 이 논문에서는 CAMshift 알고리즘과 칼만 필터(Kalman filter) 알고리즘을 결합하여 강건하게 개선된 추적모듈에 관해서 기술한다. 물체를 추적할 때 사용되는 CAMshift 알고리즘은 추적과정에서 탐색 윈도우를 설정할 때 물체가 이동하는 방향 및 속도를 고려하지 않는다는 단점이 있었다. 이를 해결하기 위해 칼만 필터 알고리즘을 추가한다면 현재 물체의 위치 및 속도 등의 정보를 바탕으로 다음 순간의 물체 위치를 추정할 수 있게 된다. 이 추정값을 기준으로 CAMshift 추적 시 탐색 윈도우를 재설정함으로써, 기존 CAMshift 알고리즘만으로는 추적이 불가능한 고속 이동물체에 대해서도 보다 정확한 추적이 가능하게 되었다. 또 본 연구에서는 추적 대상의 HSV와 YCrCb 두 색상정보를 동시에 고려함으로써 단일 색정보를 이용하는 검출보다 더 강인한 결과를 얻을 수 있었다.

Direct tracking of noncircular sources for multiple arrays via improved unscented particle filter method

  • Yang Qian;Xinlei Shi;Haowei Zeng;Mushtaq Ahmad
    • ETRI Journal
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    • 제45권3호
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    • pp.394-403
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    • 2023
  • Direct tracking problem of moving noncircular sources for multiple arrays is investigated in this study. Here, we propose an improved unscented particle filter (I-UPF) direct tracking method, which combines system proportional symmetry unscented particle filter and Markov Chain Monte Carlo (MCMC) algorithm. Noncircular sources can extend the dimension of sources matrix, and the direct tracking accuracy is improved. This method uses multiple arrays to receive sources. Firstly, set up a direct tracking model through consecutive time and Doppler information. Subsequently, based on the improved unscented particle filter algorithm, the proposed tracking model is to improve the direct tracking accuracy and reduce computational complexity. Simulation results show that the proposed improved unscented particle filter algorithm for noncircular sources has enhanced tracking accuracy than Markov Chain Monte Carlo unscented particle filter algorithm, Markov Chain Monte Carlo extended Kalman particle filter, and two-step tracking method.

Modelling and Performance Analysis of UPQC with Digital Kalman Control Algorithm under Unbalanced Distorted Source Voltage conditions

  • Kumar, Venkateshv;Ramachandran, Rajeswari
    • Journal of Power Electronics
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    • 제18권6호
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    • pp.1830-1843
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    • 2018
  • In this paper, the generation of a reference current and voltage signal based on a Kalman filter is offered for a 3-phase 4wire UPQC (Unified Power Quality Conditioner). The performance of the UPQC is improved with source voltages that are distorted due to harmonic components. Despite harmonic and frequency variations, the Kalman filter is capable enough to determine the amplitude and the phase angle of load currents and source voltages. The calculation of the first state is sufficient to identify the fundamental components of the current, voltage and angle. Therefore, the Kalman state estimator is fast and simple. A Kalman based control strategy is proposed and implemented for a UPQC in a distribution system. The performance of the proposed control strategy is assessed for all possible source conditions with varying nonlinear and linear loads. The functioning of the proposed control algorithm with a UPQC is scrutinized and validated through simulations employing MATLAB/Simulink software. Using a FPGA SPATRAN 3A DSP board, the proposed algorithm is developed and implemented. A small-scale laboratory prototype is built to verify the simulation results. The stated control scheme for the UPQC reduces the following issues, voltage sags, voltage swells, harmonic distortions (voltage and current), unbalanced supply voltage and unbalanced power factor under dynamic and steady-state operating conditions.