와이파이 수신신호세기를 사용하는 실내위치추정의 성능 향상을 위한 수정된 잔차 기반 확장 칼만 필터

조성윤,Cho, Seong Yun 제어로봇시스템학회 2015 제어·로봇·시스템학회 논문지 Vol.21 No.7

This paper presents a modified residual-based EKF (Extended Kalman Filter) for performance improvement of indoor positioning using WiFi RSSI (Received Signal Strength Indicator) measurement. Radio signal strength in indoor environments may have irregular attenuation characteristics due to obstacles such as walls, furniture, etc. Therefore, the performance of the RSSI-based positioning with the conventional trilateration method or Kalman filter is insufficient to provide location-based accurate information services. In order to enhance the performance of indoor positioning, in this paper, error analysis of the distance calculated by using the WiFi RSSI measurement is performed based on the radio propagation model. Then, an IARM (Irregularly Attenuated RSSI Measurement) error is defined. Also, it shows that the IARM error is included in the residual of the positioning filter. The IARM error is always positive. So, it is presented that the IARM error can be estimated by taking the absolute value of the residual. Consequently, accurate positioning can be achieved based on the IEM (IARM Error Mitigated) EKF with the residual modified by using the estimated IARM error. The performance of the presented IEM EKF is verified experimentally.

Nonlinear Filters

Seong Yun Cho(조성윤) 제어로봇시스템학회 2014 제어로봇시스템학회 국제학술대회 논문집 Vol.2014 No.10

보행항법장치의 모델링 및 오차 보정

趙星閏(Seong Yun Cho),朴贊國(Chan Gook Park) 대한전기학회 2002 전기학회논문지 D Vol.51 No.6

RSRP 측정치와 가상 기준위치 기반 LTE 기지국 위치추정

조성윤(Seong Yun Cho) 한국통신학회 2022 한국통신학회 학술대회논문집 Vol.2022 No.2

본 논문에서는 LTE 신호 기반 위치추정을 위해 LTE 기지국의 위치를 추정하는 기법을 설명한다. LTE 신호획득 단말기를 사용하여 획득된 LTE 신호의 RSRP 측정치와 획득 위치정보를 사용하며, 다수의 가상 기준위치를 기반으로 신호전파 모델과 LTE 기지국 정보를 함께 추정한다. 제안된 기법의 성능은 실험을 통해 분석한다.

다중속도 INS/GPS 결합항법시스템의 실시간 구현을 고려한 수정된 UKF

조성윤(Seong Yun Cho),문흐줄(Munkhzul Enkhtur),김경호(Kyong-Ho Kim) 제어로봇시스템학회 2013 제어·로봇·시스템학회 논문지 Vol.19 No.2

UKF (Unscented Kalman Filter) has been used in the nonlinear systems without initial accurate state estimates instead of EKF (Extended Kalman Filter) of the last decade because the UKF has robustness to the large initial estimation error. In the multi-rate integrated system such as INS (Inertial Navigation System)/GPS (Global Positioning System) integrated navigation system, however, it is difficult to implement the UKF based navigation algorithm in the mid-grade micro-processor due to the large computational burden. To overcome this problem, this paper proposes a MUKF (Modified UKF) that has a reduced computation burden using the basic idea that the change of the provability distribution for the state variables between measurement updates is small in the multi-rate INS/GPS integrated navigation filter. The performance of the proposed MUKF is verified by numerical simulations

차량용 INS/GPS 결합시스템의 가관측성 분석 및 다중 차수 필터 설계

조성윤(Seong Yun Cho) 제어로봇시스템학회 2008 제어·로봇·시스템학회 논문지 Vol.14 No.7

In this paper, the observability of the INS/GPS integrated system for a land vehicle is analyzed on measurements and different filters with respect to the measurements are designed. In the stationary case, it is shown that horizontal accelerometer biases and vertical attitude errors and gyro biases are unobservable. An 8-state filter is designed based on the observability analysis. When GPS signal is available, a 15-state filter is used with position and velocity measurements. To estimate the INS errors even in the case that GPS signal is blocked a filter is designed in consideration of the non-holonomic constraints of a land vehicle. In this case, the horizontal position and velocity errors and vertical attitude error are unobservable. However, a 12-state filter including the velocity states is designed to estimate the accelerometer biases. When GPS signal recovers, a 9-state filter is used excluding the sensor biases. This paper presents a multi-dimensional filter that switches the four filters according to the usable measurements and maneuver environments. A simulation is carried out to verify the performance of the proposed filter.

2 축 가속도계 기반 지자기 센서 모듈의 교정 및 가속도계 오차에 의한 방위각 계산 오차 분석

조성윤(Seong Yun Cho) 제어로봇시스템학회 2014 제어·로봇·시스템학회 논문지 Vol.20 No.2

A magnetic compass module must be calibrated accurately before use. Moreover, the calibration process must be performed taking into account any magnetic dip if the magnetic compass module has tilt angles. For this, a calibration method for a magnetic compass module is explained. Tilt error of the magnetic compass module is compensated using a biaxial accelerometer generally. The accelerometer error causes a tilt angle calculation error that gives rise to an azimuth calculation error. For error property analysis, error equations are derived and simulations are performed. In the simulation results, the accuracy of derived error equations is verified. If a biaxial magnetic compass module is used instead of a triaxial one, the magnetic dip and z-axis magnetic compass data must be estimated for tilt compensation. Lastly, estimation equations for the magnetic dip and z-axis magnetic compass data are derived, and the performance of the equations is verified based on a simulation.

거리정보 기반 무선위치추정을 위한 혼합 폐쇄형 해

조성윤(Seong Yun Cho) 제어로봇시스템학회 2013 제어·로봇·시스템학회 논문지 Vol.19 No.7

Several estimation methods used in the range measurement based wireless localization area have individual problems. These problems may not occur according to certain application areas. However, these problems may give rise to serious problems in particular applications. In this paper, three methods, ILS (Iterative Least Squares), DS (Direct Solution), and DSRM (Difference of Squared Range Measurements) methods are considered. Problems that can occur in these methods are defined and a simple hybrid solution is presented to solve them. The ILS method is the most frequently used method in wireless localization and has local minimum problems and a large computational burden compared with closed-form solutions. The DS method requires less processing time than the ILS method. However, a solution for this method may include a complex number caused by the relations between the location of reference nodes and range measurement errors. In the near-field region of the complex solution, large estimation errors occur. In the DSRM method, large measurement errors occur when the mobile node is far from the reference nodes due to the combination of range measurement error and range data. This creates the problem of large localization errors. In this paper, these problems are defined and a hybrid localization method is presented to avoid them by integrating the DS and DSRM methods. The defined problems are confirmed and the performance of the presented method is verified by a Monte-Carlo simulation.

퍼지기반 융합 무선위치추정기법

조성윤(Seong-Yun Cho) 한국전자통신학회 2015 한국전자통신학회 논문지 Vol.10 No.4

거리 측정정보를 사용하는 무선위치추정시스템에서 추정기법으로 반복기법기반 근사해를 주로 많이 사용하고 있으나 지역최소문제 및 계산량을 고려해 대안으로 선형 닫힌 형태의 해가 연구되어 왔다. 그러나 각 닫힌형태의 해는 별도의 특성을 가진 오차요인을 갖고 있으며 이 문제로 인해 그 사용이 제한되기도 한다. 본 논문에서는 대표적인 두 닫힌 형태의 해를 융합하여 각 해가 갖는 오차요인을 서로 상쇄시키는 기법을 제안한다. 두 해를 융합하기 위한 가중치를 각 오차요인이 갖는 오차 특성 기반 퍼지 기법으로 결정하는 방법을 사용한다. 제안된 기법의 성능은 시뮬레이션 기반으로 검증한다. In the wireless localization systems using range measurements, iteration method-based approximated solutions have been used. Also, linear closed-form solutions have been investigated in the light of local minimum problem and computational load. However, each closed-form solution has individual error factors that cause usage limit of the solutions. In this paper, a fusion method integrating two representative closed-form solutions is presented. The presented method cancels the error factors of each solution out. Weights for integrating the standalone solutions are determined using the error factors-based fuzzy method. The performance of the proposed method is verified using some simulation results.

모델링 불확실성을 갖는 이산구조 비선형 시스템을 위한 유한 임펄스 응답 고정구간 스무딩 필터 및 DR/GPS 결합항법 시스템에 적용

조성윤(Seong Yun Cho),김경호(Kyong-Ho Kim) 제어로봇시스템학회 2013 제어·로봇·시스템학회 논문지 Vol.19 No.5

This paper presents an FIR (Finite Impulse Response) fixed-interval smoothing filter for fast and exact estimating state variables of a discrete nonlinear system with modeling uncertainty. Conventional IIR (Infinite Impulse Response) filter and smoothing filter can estimate state variables of a system with an exact model when the system is observable. When there is an uncertainty in the system model, however, conventional IIR filter and smoothing filter may cause large errors because the filters cannot estimate the state variables corresponding to the uncertain model exactly. To solve this problem, FIR filters that have fast estimation properties and have robustness to the modeling uncertainty have been developed. However, there is time-delay estimation phenomenon in the FIR filter. The FIR smoothing filter proposed in this paper makes up for the drawbacks of the IIR filter, IIR smoothing filter, and FIR filter. Therefore, the FIR smoothing filter has good estimation performance irrespective of modeling uncertainty. The proposed FIR smoothing filter is applied to the integrated navigation system composed of a magnetic compass based DR (Dead Reckoning) and a GPS (Global Positioning System) receiver. Even when the magnetic compass error that changes largely as the surrounding magnetic field is modeled as a random constant, it is shown that the FIR smoothing filter can estimate the varying magnetic compass error fast and exactly with simulation results.