• Title/Summary/Keyword: Precision Navigation

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Parameter Estimation for Multipath Error in GPS Dual Frequency Carrier Phase Measurements Using Unscented Kalman Filters

  • Lee, Eun-Sung;Chun, Se-Bum;Lee, Young-Jae;Kang, Tea-Sam;Jee, Gyu-In;Kim, Jeong-Rae
    • International Journal of Control, Automation, and Systems
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    • v.5 no.4
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    • pp.388-396
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    • 2007
  • This paper describes a multipath estimation method for Global Positioning System (GPS) dual frequency carrier phase measurements. Multipath is a major error source in high precision GPS applications, i.e., carrier phase measurements for precise positioning and attitude determinations. In order to estimate and remove multipath at carrier phase measurements, an array GPS antenna system has been used. The known geometry between the antennas is used to estimate multipath parameters. Dual frequency carrier phase measurements increase the redundancy of measurements, so it can reduce the number of antennas. The unscented Kalman filter (UKF) is recently applied to many areas to overcome some of the limitations of the extended Kalman filter (EKF) such as weakness to severe nonlinearity. This paper uses the UKF for estimating multipath parameters. A series of simulations were performed with GPS antenna arrays located on a straight line with one reflector. The geometry information of the antenna array reduces the number of estimated multipath parameters from four to three. Both the EKF and the UKF are used as estimation algorithms and the results of the EKF and the UKF are compared. When the initial parameters are far from true parameters, the UKF shows better performance than the EKF.

Outdoor Positioning Estimation of Multi-GPS / INS Integrated System by EKF / UPF Filter Conversion (EKF/UPF필터 변환을 통한 Multi-GPS/INS 융합 시스템의 실외 위치추정)

  • Choi, Seung-Hwan;Kim, Gi-Jeung;Kim, Yun-Ki;Lee, Jang-Myung
    • Journal of Institute of Control, Robotics and Systems
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    • v.20 no.12
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    • pp.1284-1289
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    • 2014
  • In this Paper, outdoor position estimation system was implemented using GPS (Global Positioning System) and INS (Inertial Navigation System). GPS position information has lots of errors by interference from obstacles and weather, the surrounding environment. To reduce these errors, multiple GPS system is used. Also, the Discrete Wavelet Transforms was applied to INS data for compensation of its error. In this paper, position estimation of the mobile robot in the straight line is conducted by EKF (Extended Kalman Filter). However, curve running position estimation is less accurate than straight line due to phase change in rotation. The curve is recognized through the rate of change in heading angle and the position estimation precision of the initial curve was improved by UPF (Unscented Particle Filter). In the case of UPF, if the number of particle is so many that big memory gets size is needed and processing speed becomes late. So, it only used the position estimation in the initial curve. Thereafter, the position of mobile robot in curve is estimated through switching from UPF to EKF again. Through the experiments, we verify the superiority of the system and make a conclusion.

A Performance of Positioning Accuracy Improvement Scheme using Wavelet Denoising Filter (Wavelet Denoising Filter를 이용한 측위 정밀도 향상 기법 성능)

  • Shin, Dong Soo;Park, Ji Ho;Park, Young Sik;Hwang, Yu Min;Kim, Jin Young
    • Journal of Satellite, Information and Communications
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    • v.9 no.3
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    • pp.9-14
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    • 2014
  • Recently, precision guided munition systems and missile defense systems based on GPS have been taking a key role in modern warfare. In warfare however, unexpected interferences cause by large/small scale fading, radio frequency interferences, etc. These interferences result in a severe GPS positioning error, which could occur late supports and friendly fires. To solve the problems, this paper proposes an interference mitigation positioning method by adopting a wavelet denoising filter algorithm. The algorithm is applied to a GPS/QZSS/Wi-Fi combined positioning system which was performed by this laboratory. Experimental results of this paper are based on a real field test data of a GPS/QZSS/Wi-Fi combined positioning system and a simulation data of a wavelet denoising filter algorithm. At the end, the simulation result demonstrates its superiority by showing a 21.6% improved result in comparison to a conventional GPS system.

Relative Localization for Mobile Robot using 3D Reconstruction of Scale-Invariant Features (스케일불변 특징의 삼차원 재구성을 통한 이동 로봇의 상대위치추정)

  • Kil, Se-Kee;Lee, Jong-Shill;Ryu, Je-Goon;Lee, Eung-Hyuk;Hong, Seung-Hong;Shen, Dong-Fan
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.55 no.4
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    • pp.173-180
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    • 2006
  • A key component of autonomous navigation of intelligent home robot is localization and map building with recognized features from the environment. To validate this, accurate measurement of relative location between robot and features is essential. In this paper, we proposed relative localization algorithm based on 3D reconstruction of scale invariant features of two images which are captured from two parallel cameras. We captured two images from parallel cameras which are attached in front of robot and detect scale invariant features in each image using SIFT(scale invariant feature transform). Then, we performed matching for the two image's feature points and got the relative location using 3D reconstruction for the matched points. Stereo camera needs high precision of two camera's extrinsic and matching pixels in two camera image. Because we used two cameras which are different from stereo camera and scale invariant feature point and it's easy to setup the extrinsic parameter. Furthermore, 3D reconstruction does not need any other sensor. And the results can be simultaneously used by obstacle avoidance, map building and localization. We set 20cm the distance between two camera and capture the 3frames per second. The experimental results show :t6cm maximum error in the range of less than 2m and ${\pm}15cm$ maximum error in the range of between 2m and 4m.

Intentional GNSS Interference Detection and Characterization Algorithm Using AGC and Adaptive IIR Notch Filter

  • Yang, Jeong Hwan;Kang, Chang Ho;Kim, Sun Young;Park, Chan Gook
    • International Journal of Aeronautical and Space Sciences
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    • v.13 no.4
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    • pp.491-498
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    • 2012
  • A Ground Based Augmentation System (GBAS) is an enabling technology for an aircraft's precision approach based on a Global Navigation Satellite System (GNSS). However, GBAS is vulnerable to interference, so effective GNSS interference detection and mitigation methods need to be employed. In this paper, an intentional GNSS interference detection and characterization algorithm is proposed. The algorithm uses Automatic Gain Control (AGC) gain and adaptive notch filter parameters to classify types of incoming interference and to characterize them. The AGC gain and adaptive lattice IIR notch filter parameter values in GNSS receivers are examined according to interference types and power levels. Based on those data, the interference detection and characterization algorithm is developed and Monte Carlo simulations are carried out for performance analysis of the proposed method. Here, the proposed algorithm is used to detect and characterize single-tone continuous wave interference, swept continuous wave interference, and band-limited white Gaussian noise. The algorithm can be used for GNSS interference monitoring in an excessive Radio Frequency Interference environment which causes loss of receiver tracking. This interference detection and characterization algorithm will be used to enhance the interference mitigation algorithm.

Performance Improvement Technique of Three-Dimensional Guidance Law Suitable for Ammunition (포발사 탄약에 적합한 3차원 유도법칙의 성능개선 기법)

  • Shin, Seung-Je;Kim, Whan-Woo
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.46 no.8
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    • pp.631-638
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    • 2018
  • In this paper, we propose a method to improve the performance by guidance technique and applying it to the precision guided ammunition. The proposed method is a technique designed to reduce the target error of ammunition by reducing the projectile error without analyzing the motion characteristics of the shot. This technique is applied to the moving average filter technique which is widely used as signal processing technique to reduce the fluctuation of the output of the inboard mounting inertial sensor caused by the rotation and the coning motion of the ammunition. In order to compare the performance of the applied technique including the simple 3D guided control technique and the proposed improvement technique. It is confirmed that the application of this technique improves the accuracy of impact of the cannon - launched ammunition with severe environmental conditions and irregular motion characteristics unlike the missile.

Development of Flight Control System for Gliding Guided Artillery Munition - Part II : Guidance and Control (유도형 활공 탄약 비행제어시스템 개발 Part II : 유도 및 제어)

  • Lim, Seunghan;Pak, Changho;Cho, Changyeon;Bang, Hyochoong
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.42 no.3
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    • pp.229-236
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    • 2014
  • In this paper, the guidance laws and controllers for the gliding guided artillery munition is studied. The gliding guided artillery munition has wings for gliding to increase a range; therefore previous guidance laws and controllers for the guided munition could not be applied. Concepts of vector field guidance and proportional navigation guidance are applied for mid-term and terminal guidance, respectively. The gliding guided artillery munition is operated within wide altitude and speed areas; therefore, the controllers are designed for each area, and gain-scheduling and the linear interpolation technique is applied to compute the appropriate gains.

Vehicle Dynamics and Road Slope Estimation based on Cascade Extended Kalman Filter (Cascade Extended Kalman Filter 기반의 차량동특성 및 도로종단경사 추정)

  • Kim, Moon-Sik;Kim, Chang-Il;Lee, Kwang-Soo
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.9
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    • pp.208-214
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    • 2014
  • Vehicle dynamic states used in various advanced driving safety systems are influenced by road geometry. Among the road geometry information, the vehicle pitch angle influenced by road slope and acceleration-deceleration is essential parameter used in pose estimation including the navigation system, advanced adaptive cruise control and others on sag road. Although the road slope data is essential parameter, the method measuring the parameter is not commercialized. The digital map including the road geometry data and high-precision DGPS system such as DGPS(Differential Global Positioning System) based RTK(Real-Time Kinematics) are used unusually. In this paper, low-cost cascade extended Kalman filter(CEKF) based road slope estimation method is proposed. It use cascade two EKFs. The EKFs use several measured vehicle states such as yaw rate, longitudinal acceleration, lateral acceleration and wheel speed of the rear tires and 3 D.O.F(Degree Of Freedom) vehicle dynamics model. The performance of proposed estimation algorithm is evaluated by simulation based on Carsim dynamics tool and T-car based experiment.

Moving Path following and High Speed Precision Control of Autonomous Mobile Robot Using Fuzzy (퍼지를 이용한 자율 이동 로봇의 이동 경로 추종 및 고속 정밀 제어)

  • Lee, Won-Ho;Lee, Hyung-Woo;Kim, Sang-Heon;Jung, Jae-Young;Roh, Tae-Jung
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.7
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    • pp.907-913
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    • 2004
  • The major interest of general mobile robot is making a route and following a maked route. But, In the case of robot that is in need of movement of partial high speed, the condition of dynamic limitation is exist, and in these conditions, it demands controlling against movements we want. In this paper, in respect of the following a route at the situation that don't have the environmental map, that is, unknown environments, to prevent the slide of moving robot or the overturn that can happen for it moves fast, we organize the dynamic condition of limitation using the fuzzy logic, and we obtain more safe and fast route tracing ability by changing the standard velocity. Especially, by modeling the line tracing mobile robot, we design the tracing controller against a realtime changing target, and using the fuzzy optimized velocity limitation controller, we confirm that our robot shows its stable tracing ability by limiting its velocity intelligently against the continuously changing line.

Accuracy Assessment of the Upward Continuation using the Gravity Model from Ultra-high Degree Spherical Harmonics (초 고차항 구 조화 중력모델링에 의한 상향 연속의 정확도 검증)

  • Kwon Jay-Hyoun;Lee Jong-Ki
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.24 no.2
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    • pp.183-191
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    • 2006
  • The accuracy of the upward continuation is assessed through the gravity modeling using an ultra-high degree spherical harmonic expansion. The difficulties in the numerical calculation of Legendre function with ultra-high degree, underflow and/or overflow, is successfully resolved in 128 bit calculation scheme. Using the generated Legendre function, the gravity anomaly with spatial resolution of $1'{\times}1'$ on the geoid is calculated. The generated gravity anomaly is degraded and extracted with various noise levels and data intervals, then upward continuation is applied to each data sets. The comparison between the upward continued gravity disturbances and the directly calculated from the spherical harmonics showed that the accuracy on the direct method was significantly better than that of Poisson method. In addition, it is verified that the denser and less noised gravity data on the geoid generates better gravity disturbance vectors at an altitude. Especially, it is found that the gravity noise level less than 5mGal, and the data interval less than 2arcmin is necessary for next generation precision INS navigation which requires the accuracy of 5mGal or better at an altitude.