• Journal of Advanced Navigation Technology
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• v.15 no.4
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• pp.556-561
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• 2011

It is generally known that particle filters can produce consistent target tracking performance in comparison to the Kalman filter for non-linear and non-Gaussian systems. In this paper, I propose a Rao-Blackwellized multiple model particle filter(RBMMPF) to enhance computational efficiency of the particle filters as well as to reduce sensitivity of modeling. Despite that the Rao-Blackwellized particle filter needs less particles than general particle filter, it has a similar tracking performance with a less computational load. Comparison results for performance is listed for the using single sensor information RBMMPF and using multisensor data fusion RBMMPF.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.173-182
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• 2005

In this paper, a target tracking algorithm for tracking maneuvering vehicles is presented. The overall algorithm belongs to the category of an interacting multiple-model (IMM) algorithm used to detect multiple targets using fused information from multiple sensors. First, two kinematic models are derived: a constant velocity model for linear motions, and a constant-speed turn model for curvilinear motions. Fpr the constant-speed turn model, a nonlinear information filter is used in place of the extended Kalman filter. Being equivalent to the Kalman filter (KF) algebraically, the information filter is extended to N-sensor distributed dynamic systems. The model-matched filter used in multi-sensor environments takes the form of a federated nonlinear information filter. In multi-sensor environments, the information-based filter is easier to decentralize, initialize, and fuse than a KF-based filter. In this paper, the structural features and information sharing principle of the federated information filter are discussed. The performance of the suggested algorithm using a Monte Carlo simulation under the two patterns is evaluated.

• ETRI Journal
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• v.45 no.3
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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.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.5
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• pp.445-453
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• 2001

The multiple targets tracking problem has been one of the main issues in the radar applications area in the last decade. Besides the standard Kalman filtering, various methods including the variable dimen-sion filter, input estimation filter, interacting multiple model(IMM) filter, dederated variable dimension filter with input estimation, etc., have proposed to address the tracking and sensor fusion issues. In this pa- per, two existing tracking algorithm, i.e, the IMM filter and the variable dimension filter with input estima-tion(VDIE), are combined for the purpose of improving the tracking performance for maneuvering targets. To evaluate the tracking performance of the proposed algorithm, three typical maneuvering patterns, i.e., waver, pop-up, and high-diver motions, are defined and are applied to the modified IMM filter as well as the standard IMM filter. The smaller RMS tracking errors, in position and velocity, of the modified IMM filter than the standard IMM filter are demonstrated though computer simulations.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.12
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• pp.2046-2054
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• 1989

Improved algorithms are presented to design linear phase digital FIR filters with coefficients of +1,0,-1 only followed by a multiple integrator. It has been shown that the existing linear phase filter design concept for the single integrator(or, accumulator)case can be extended to the case of the multiple integrator. Linear phase conditions for the multiple integrators are summarized. Filter design methods with double or triple integrator are exploited in datail and its computer simulation results are presented to deduce the advantages of multiple integrator to the single integrator.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.1
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• pp.130-136
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• 1990

For the rotation-invariant pattern recognition, we propose multiple circular harmonic filter which is expanded about the proper center. The proper centerm when input image is given, is the circular harmonic expansion center of the filter which yields a maximum center correlation peak in the output plane. In this paper, we founded the circular harmonic components that the proper center superposes on the same position and then designed multiple circular harmonic filter using these components. Also the proposed filter is compared with conventional multiple circular harmonic filter and shows that it can maximize the center correlation peak for the rotated input image by the computer simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.5A
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• pp.494-499
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• 2008

In this study, a Software Defined Radio(SDR) technology-based digital filtering technique applicable to a multiple channel processing system such as a wireless mobile communication system using Code Division Multiple Access(CDMA) technology is proposed. The technique includes a micro-processor to redesign Finite Impulse Response(FIR) filter coefficients according to specific system information and to download the filter coefficients to one digital Band Pass Filter(BPF) to reconfigure another system. The feasibility of the algorithm is verified by implementing a multiple channel signal generator that is reconfigurable to other system profiles, including those for a CDMA system and a WCDMA system on identical hardware platform.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2340-2344
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• 2003

This paper considers a tracking filter algorithm which can track a maneuvering target. Multiresolutional Interacting Multiple Model (MRIMM) algorithm is proposed to reduce computational burden. In this paper multiresolutional state space model equation and multiresolutional measurement equation are derived by using wavelet transform. This paper shows the outline of MRIMM algorithm. Simulation results show that MRIMM algorithm maintains a good tracking performance and reduces computational burden.

• Journal of Ubiquitous Convergence Technology
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• v.2 no.2
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• pp.59-66
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• 2008

In this study, Software Defined Radio (SDR) technology-based digital filterbank architecture applicable to a multiple-channel processing system such as a wireless mobile communication system using Code Division Multiple Access (CDMA) technology is proposed. The technique includes a micro-processor to redesign Finite Impulse Response (FIR) filter coefficients according to specific system information and to download the filter coefficients to one digital Band Pass Filter (BPF) to reconfigure another system. The feasibility of the algorithm is verified by computer simulation and by implementing a multiple-channel signal generator that is reconfigurable to other system profiles, including those of a Wideband Code Division Multiple Access (WCDMA) system and a CDMA system.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.211-211
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• 2000

The multiple targets tracking problem has been one of main issues in the radar applications area in the last decade. Besides the standard Kalman filtering, various methods including the variable dimension filter, input estimation filter, interacting multiple model (IMM) filter, federated variable dimension filter with input estimation, probable data association (PDA) filter etc. have been proposed to address the tracking and sensor fusion issues. In this paper, two existing tracking algorithms, i.e. the IMMPDA filter and the variable dimension filter with input estimation (VDIE), are combined for the purpose of improving the tracking performance of maneuvering targets in clutter. To evaluate the tracking performance of the proposed algorithm, three typical maneuvering patterns i.e. Waver, Pop-Up, and High-Diver motions, are defined and are applied to the modified IMMPDA filter considered as well as the standard IMM filter. The smaller RMS tracking errors, in position and velocity, of the modified IMMPDA filter than the standard IMM filter are demonstrated through computer simulations.