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1

Zastosowanie filtracji cząsteczkowej do estymacji położenia w systemie lokalizacyjnym UWB

Magiera Jarosław

Przegląd Telekomunikacyjny + Wiadomości Telekomunikacyjne

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2019

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nr 6

249--252, CD

PL

Niniejszy artykuł dotyczy kwestii poprawy dokładności estymacji położenia w systemie lokalizacji wewnątrzbudynkowej, bazującym na radiowych pomiarach odległości realizowanych przez modemy UWB. Proponuje się zastosowanie metody filtracji cząsteczkowej do zmniejszenia błędu wyznaczania pozycji obiektu przy braku bezpośredniej widoczności ze stacją referencyjną. W artykule opisano algorytm filtru cząsteczkowego, jego przykładową implementację oraz weryfikację z użyciem rzeczywistych danych pomiarowych.

EN

This paper is related to improvement of location estimation accuracy in indoor positioning system based on radio ranging using UWB modems. Author propose to apply particle filtering method to decrease the position estimation error when there is no direct line of sight to reference station. The paper presents particle filter algorithm, its sample implementation and verification using real measurement data.

2

The new approach to hybrid Kalman filtering, based on the changed order of filters for state estimation of dynamical systems

Michalski Jacek, Kozierski Piotr, Ziętkiewicz Joanna

Poznan University of Technology Academic Journals. Electrical Engineering

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2019

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No. 97

181--190

EN

The paper presents a new approach to Hybrid Kalman filtering, composed of Extended Kalman Filter and Unscented Kalman Filter. In known algorithms, the Unscented Kalman Filter algorithm is used as first and the result of this is given as an input to the Extended Kalman Filter. The authors checked modified Hybrid Kalman Filter with changed order of filters using theoretical object, which was created on the basis of power system. Besides traditional method, the modification of Hybrid Kalman Particle Filter was evaluated too. Results were compared with Extended Kalman Filter, Unscented Kalman Filter and Bootstrap Particle Filter. For particle filters the authors compared method estimation qualities for a different number of particles. The estimation quality was evaluated by three quality indices. Based on the obtained results, one can see that the changed order of methods in Hybrid Kalman filter can improve estimation quality.

3

Population Monte Carlo and Adaptive Importance Sampling in particle filter

Kozierski P.

Studia z Automatyki i Informatyki

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2014

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T. 39

33--41

EN

Population Monte Carlo and Adaptive Importance Sampling methods have been presented and compared in the paper. The impact of parameters on the estimation quality of the plant also has been studied.

PL

W artykule przedstawiono i porównano metody Populacja Monte Carlo oraz Adaptacyjna Funkcja Ważności. Sprawdzono również wpływ parametrów tych metod na jakość estymacji stanu obiektu.

4

Particle filtering for computer vision-based identification of frame model parameters

Tekieli M., Słoński M.

Computer Assisted Methods in Engineering and Science

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2014

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Vol. 21, no. 1

39--48

EN

In this paper we present a new approach for solving identification problems based on a novel combination of computer vision techniques, Bayesian state estimation and finite element method. Using our approach we solved two identification problems for a laboratory-scale aluminum frame. In the first problem, we recursively estimated the elastic modulus of the frame material. In the second problem, for the known elastic constant, we identified sequentially the position of a quasi-static concentrated load.

5

Fusion of data from inertial sensors, raster maps and GPS for estimation of pedestrian geographic location in urban terrain

Barański P., Polańczyk M., Strumiłło P.

Metrology and Measurement Systems

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2011

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Vol. 18, nr 1

145-157

EN

An electronic system and an algorithm for estimating pedestrian geographic location in urban terrain is reported in the paper. Different sources of kinematic and positioning data are acquired (i.e.: accelerometer, gyroscope, GPS receiver, raster maps of terrain) and jointly processed by a Monte-Carlo simulation algorithm based on the particle filtering scheme. These data are processed and fused to estimate the most probable geographical location of the user. A prototype system was designed, built and tested with a view to aiding blind pedestrians. It was shown in the conducted field trials that the method yields superior results to sole GPS readouts. Moreover, the estimated location of the user can be effectively sustained when GPS fixes are not available (e.g. tunnels).

6

Face Tracking and Recognition with the Use of Particle-Filtered Local Features

Stasiak Ł. A., Pacut A.

Journal of Telecommunications and Information Technology

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2010

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nr 4

26-36

EN

A consistent particle filtering-based framework for the purpose of parallel face tracking and recognition from video sequences is proposed. A novel approach to defining randomized, particle filtering-driven local face features for the purpose of recognition is proposed. The potential of cumulating classification decisions based on the proposed feature set definition is evaluated. By applying cumulation mechanisms to the classification results determined from single frames and with the use of particle-filtered features, good recognition rates are obtained at the minimal computational cost. The proposed framework can operate in real-time on a typical modern PC. Additionally, the application of cumulation mechanisms makes the framework resistant to brief visual distortions, such as occlusions, head rotations or face expressions. A high performance is also obtained on low resolution images (video frames). Since the framework is based on the particle filtering principle, it is easily tunable to various application requirements (security level, hardware constraints).

7

Zastosowanie czujników inercyjnych i metody Monte Carlo do korekcji odczytów GPS w terenie miejskim

Barański R., Polańczyk M., Strumiłło R.

Elektronika : konstrukcje, technologie, zastosowania

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2010

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Vol. 51, nr 10

115-118

PL

W artykule omówiono zastosowanie symulacyjnej metody Monte Carlo do poprawy dokładności odczytów GPS (ang. Global Positioning System) w terenie miejskim. Zaprojektowany układ elektroniczny jest elementem systemu do nawigacji pieszej osób niewidomych. W terenie miejskim, na skutek odbić i wielodrogowości sygnałów od satelitów, odczyty GPS są obarczone znacznym błędem dochodzącym do kilkudziesięciu metrów. Jednoczesne odczyty z akcelerometru oraz żyroskopu służą do pomiaru względnego przemieszczenia, a następnie są porównywane z odczytami GPS. Algorytm symulacji wykorzystujący metodę Monte Carlo, służy do wyznaczenia najbardziej prawdopodobnego położenia geograficznego. Zastosowany układ umożliwia nawet kilkukrotne zmniejszenie błędu wyznaczanego położenia geograficznego.

EN

The article presents an application of recursive Monte Carlo method for correcting GPS readouts in an urban environment. The prototype was designed with a view of a pedestrian navigation device for the blind. GPS readouts are at times very inaccurate in an urban environment (reaching several dozens of meters) due to multipath propagation and reflections from buildings, The device houses an accelerometer and gyroscope for estimating the relative motion of the device. This relative displacement is correlated with GPS readouts. An algorithm based on the Monte Carlo simulation is used for assessing the most probable geographical location of the user. From the urban test of the method we conclude that the pro-posed dead reckoning solution improves on GPS receiver readouts by several times.

8

Particle filtering for the estimation of system mode of operation

Cadini F., Avram D., Zio E.

Journal of Polish Safety and Reliability Association

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2009

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Vol. 1

77--86

EN

Efficient diagnosis and prognosis of system faults depend on the ability to estimate the system state on the basis of noisy measurements of the system dynamic variables and parameters. The system dynamics is typically characterized by transitions among discrete modes of operation, each one giving rise to a specific continuous dynamics of evolution. The estimation of the state of these hybrid dynamic systems is a particularly challenging task because it requires keeping track of the transitions among the multiple modes of system dynamics corresponding to the different modes of operation. In this paper a Monte Carlo estimation method is illustrated with an application to a case study of literature which consists of a tank filled with liquid, whose level is autonomously maintained between two thresholds. The system behavior is controlled by discrete mode actuators, whose states are estimated by a Monte Carlo-based particle filter on the basis of noisy level and temperature measurements.