• Title/Summary/Keyword: Angle estimation

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A Study on Look Error Estimation and Adaptive Array Angle Estimation (지향 오차 추정과 적응 배열 입사방향 추정 방법에 대한 연구)

  • Lee, Kwan-Hyeong;Song, Woo-Young;Lee, Myung-Ho
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.9
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    • pp.155-162
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    • 2011
  • It is using to incident angle estimation technique in order to target estimation in radar. This paper was estimated incident angle estimation for target using adaptive array incident angle and single look error incident angle estimation technique. We estimated signal incident angle of target to removal main lobe and side lobe to adaptive array incident angle technique. It is difficult to correctly target estimation because single look technique increase direction error of signal incident angle. In order to receive a desired target signal must be not almost look error between signal incident angle and look angle. we had decreased to occur a look error using delay time and single look condition to calculation a covariance when incident angle estimate. Through simulation, we show that the proposed incident angle estimation technique improves the performance of target estimation compared to previous method.

ML-Based Angle-of-arrival Estimation of a Parametric Source

  • Lee, Yong-Up;Kim, Jong-Dae;Park, Joong-Hoo
    • The Journal of the Acoustical Society of Korea
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    • v.20 no.3E
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    • pp.25-30
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    • 2001
  • In angle of arrival estimation, the direction of a signal is usually assumed to be a point. If the direction of a signal is distributed due to some reasons in real surroundings, however, angle of arrival estimation techniques based on the point source assumption may result in poor performance. In this paper, we consider angle of arrival estimation when the signal sources are distributed. A parametric source model is proposed, and the estimation techniques based on the well-known maximum likelihood technique is considered under the model. In addition, Various statistical properties of the estimation errors were obtained.

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Estimating Angle-of-Arrival of UWB Cluster signals in an Indoor-to-Outdoor Wireless Communication (실내와 실외 무선통신 환경에서 초광대역 클러스터 신호의 도착 방향 추정)

  • Lee Yong-Up;Seo Young-Jun;Choi Gin-Kyu
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.31 no.5C
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    • pp.556-561
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    • 2006
  • In this study, an ultra-wideband(UWB) signal model is considered to estimate the angle-of-arrivals(AOAs) of clusters in an UWB indoor-to-outdoor communication environment having random angle spreads. A conventional AOA algorithm for UWB estimates the directions of both clusters and multipath signals together and so has complex estimation procedure. In order to solve that problem, we propose a new clustered AOA estimation algorithm. The estimation technique based a well-known MUSIC algorithm is proposed and the estimates of the AOA on received clusters are obtained using the proposed technique. The proposed model and estimation technique are verified through computer simulations.

Joint Range and Angle Estimation of FMCW MIMO Radar (FMCW MIMO 레이다를 이용한 거리-각도 동시 추정 기법)

  • Kim, Junghoon;Song, Sungchan;Chun, Joohwan
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.30 no.2
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    • pp.169-172
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    • 2019
  • Frequency-modulated continuous wave(FMCW) radars with array antennas are widely used because of their light weight and relatively high resolution. A usual approach for the joint range and angle estimation of a target using an array FMCW radar is to create a range-angle matrix with the deramped received signal, and subsequently apply two-dimensional(2D) frequency estimation methods such as 2D fast Fourier transform on the range-angle matrix. However, such frequency estimation approaches cause bias errors since the frequencies in the range-angle matrix are not independent. Therefore, we propose a new maximum likelihood-based algorithm for joint range and angle estimation of targets using array FMCW radar, and demonstrate that the proposed algorithm achieves the Cram?r-Rao bounds, both for range as well as angle estimation.

Imperfection Parameter Observer and Drift Compensation Controller Design of Hemispherical Resonator Gyros

  • Pi, Jaehwan;Bang, Hyochoong
    • International Journal of Aeronautical and Space Sciences
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    • v.14 no.4
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    • pp.379-386
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    • 2013
  • The hemispherical resonator gyroscope is a type of vibratory gyroscope, which can measure angle or angular rate, based on its operating mode. This paper deals with the case when the hemispherical resonator gyroscope is operated in angle measurement mode. In angle measurement mode, the resonator pattern angle precesses, with respect to the external rotation input, by the principle of the Coriolis effect, so that the external rotation can be estimated, by measuring the amount of precession angle. However, this pattern angle drifts, due to the manufacturing error of the resonator. Since the drift effect causes degradation of the angle estimation performance of the resonator, the corresponding drift compensation control should be performed, to enhance the estimation performance. In this paper, a mathematical model of the hemispherical resonator gyro is first introduced. By using the mathematical model, a nonlinear observer for imperfection parameter estimation, and the corresponding compensation controller are designed to operate hemispherical resonator gyros, as angle measurement sensors.

Fast-convergence trilinear decomposition algorithm for angle and range estimation in FDA-MIMO radar

  • Wang, Cheng;Zheng, Wang;Li, Jianfeng;Gong, Pan;Li, Zheng
    • ETRI Journal
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    • v.43 no.1
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    • pp.120-132
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    • 2021
  • A frequency diverse array (FDA) multiple-input multiple-output (MIMO) radar employs a small frequency increment across transmit elements to produce an angle-range-dependent beampattern for target angle and range detection. The joint angle and range estimation problem is a trilinear model. The traditional trilinear alternating least square (TALS) algorithm involves high computational load due to excessive iterations. We propose a fast-convergence trilinear decomposition (FC-TD) algorithm to jointly estimate FDA-MIMO radar target angle and range. We first use a propagator method to obtain coarse angle and range estimates in the data domain. Next, the coarse estimates are used as initialized parameters instead of the traditional TALS algorithm random initialization to reduce iterations and accelerate convergence. Finally, fine angle and range estimates are derived and automatically paired. Compared to the traditional TALS algorithm, the proposed FC-TD algorithm has lower computational complexity with no estimation performance degradation. Moreover, Cramer-Rao bounds are presented and simulation results are provided to validate the proposed FC-TD algorithm effectiveness.

Angle-Range-Polarization Estimation for Polarization Sensitive Bistatic FDA-MIMO Radar via PARAFAC Algorithm

  • Wang, Qingzhu;Yu, Dan;Zhu, Yihai
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.7
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    • pp.2879-2890
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    • 2020
  • In this paper, we study the estimation of angle, range and polarization parameters of a bistatic polarization sensitive frequency diverse array multiple-input multiple-output (PSFDA-MIMO) radar system. The application of polarization sensitive array in receiver is explored. A signal model of bistatic PSFDA-MIMO radar system is established. In order to utilize the multi-dimensional structure of array signals, the matched filtering radar data can be represented by a third-order tensor model. A joint estimation of the direction-of-departure (DOD), direction-of-arrival (DOA), range and polarization parameters based on parallel factor (PARAFAC) algorithm is proposed. The proposed algorithm does not need to search spectral peaks and singular value decomposition, and can obtain automatic pairing estimation. The method was compared with the existing methods, and the results show that the performance of the method is better. Therefore, the accuracy of the parameter estimation is further improved.

Angle Estimation Error Reduction Method Using Weighted IMM (Weighted IMM 기법을 사용한 각도 추정 오차 감소 기법)

  • Choi, Seonghee;Song, Taeklyul
    • Journal of the Korea Institute of Military Science and Technology
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    • v.18 no.1
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    • pp.84-92
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    • 2015
  • This paper proposes a new approach to reduce the target estimation error of the measurement angle, especially applied to the medium and long range surveillance radar. If the target has no maneuver and no change in heading direction for a certain time interval, the predicted angle of interacting multiple model(IMM) from the previous track information can be used to reduce the angle estimation error. The proposed method is simulated in 2 scenarios, a scenario with a non-maneuvering target and a scenario with a maneuvering target. The result shows that the new fusion solution(weighted IMM) with the predicted azimuth and the measured azimuth is worked properly in the two scenarios.

A Study on the Effect of Weighting Matrix of Robot Vision Control Algorithm in Robot Point Placement Task (점 배치 작업 시 제시된 로봇 비젼 제어알고리즘의 가중행렬의 영향에 관한 연구)

  • Son, Jae-Kyung;Jang, Wan-Shik;Sung, Yoon-Gyung
    • Journal of the Korean Society for Precision Engineering
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    • v.29 no.9
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    • pp.986-994
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    • 2012
  • This paper is concerned with the application of the vision control algorithm with weighting matrix in robot point placement task. The proposed vision control algorithm involves four models, which are the robot kinematic model, vision system model, the parameter estimation scheme and robot joint angle estimation scheme. This proposed algorithm is to make the robot move actively, even if relative position between camera and robot, and camera's focal length are unknown. The parameter estimation scheme and joint angle estimation scheme in this proposed algorithm have form of nonlinear equation. In particular, the joint angle estimation model includes several restrictive conditions. For this study, the weighting matrix which gave various weighting near the target was applied to the parameter estimation scheme. Then, this study is to investigate how this change of the weighting matrix will affect the presented vision control algorithm. Finally, the effect of the weighting matrix of robot vision control algorithm is demonstrated experimentally by performing the robot point placement.

Vehicle State Estimation Robust to Wheel Slip Using Extended Kalman Filter (휠 슬립에 강건한 확장칼만필터 기반 차량 상태 추정)

  • Myeonggeun, Jun;Ara, Jo;Kyongsu, Yi
    • Journal of Auto-vehicle Safety Association
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    • v.14 no.4
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    • pp.16-20
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    • 2022
  • Accurate state estimation is important for autonomous driving. However, the estimation error increases in situations that a lot of longitudinal slip occurs. Therefore, this paper presents a vehicle state estimation method using an Extended Kalman Filter. The filter estimates the states of the host vehicle robust to wheel slip. It utilizes the measurements of the four-wheel rotational speeds, longitudinal acceleration, yaw-rate, and steering wheel angle. Nonlinear measurement model is represented by Ackermann Model. The main advantage of this approach is the accurate estimation of yaw rate due to the measurement of the steering wheel angle. The proposed algorithm is verified in scenarios of autonomous emergency braking (AEB), lane change (LC), lane keeping (LK) using an automated vehicle. The results show that the proposed algorithm guarantees accurate estimation in such scenarios.