Kwanho You

TDoA Based UAV Localization Using Dual-EKF Algorithm

Most UAV(unmaned aerial vehicle) systems use GPS signals only to locate the emitter’s position. However GPS signals contain unwanted information contaminated by environmental components and many interference signals. In this paper, to obtain TDoA signal, we use two UAVs which are equipped with embedded wireless sensors. Under the real geolocation circumstance, it is very difficult to estimate the emitter’s position exactly due to environmental noise. In this paper we use the dual-EKF algorithm to obtain the optimal estimation of state values and unknown parameters. The dual-EKF algorithm overcomes the weakness of EKF algorithm which has been widely used in geolocation problem. The performance of our proposed algorithm will be demonstrated through some simulations of UAVs.

Channel Adaptive Power Control in the Uplink of CDMA Systems

In this paper, we propose an adaptive power control algorithm using optimal control theory for CDMA cellular systems. With linear quadratic control, each mobile transmits to achieve a desired SIR under the fast varying environment of practical CDMA cellular systems. We apply Kalman filter theory to estimate a channel variation which is vulnerable to nonconstant link gain, mutual interference and uncertain noise. Through simulation comparison with DCPC algorithm, the suggested power control algorithm shows an increased uplink channel capacity.

Adaptive neural network approach for nonlinearity compensation in laser interferometer

In this paper, we propose a compensation algorithm to reduce the nonlinearity error which is occurred in a heterodyne laser interferometer as a nano-meter scale measurement apparatus. In heterodyne laser interferometer, frequency-mixing is the main factor of nonlinearity error. Using an RLS algorithm, the nonlinearity compensation parameters are found to be used through geometric projection. With the roughly modified intensity signals from LIA, the back-propagation neural network algorithm minimizes the objective function to track the reference signal for learning period. Through some experiments, it is verified that the proposed algorithm can reduce nonlinear factors and improve the measurement accuracy of laser interferometer.

TDOA/FDOA Geolocation with Adaptive Extended Kalman Filter

In this paper, we propose a moving target tracking algorithm using the measurement signals of time difference of arrival (TDOA) and the frequency difference of arrival (FDOA). As the conventional target tracking using TDOA measurement is not accurate enough to estimate the target location, we use the TDOA and FDOA measurement signals together to estimate the location and the velocity of a target at discrete times. Although, the Kalman filter shows remarkable performance in calculation and location estimation, the estimation error can be large when the priori noise covariances are assumed with improper values. We suggest an adaptive extended Kalman filter (AEKF) to update the noise covariance at each measurement and estimation process. The simulation results show that the algorithm efficiently reduces the position error and it also greatly improves the accuracy of target tracking.

TDoA Based UGV Localization Using Adaptive Kalman Filter Algorithm

The measurement with a signal of time difference of arrival (TDoA) is a widely used technique in source localization. However, this method involves much nonlinear calculation. In this paper, we propose a method that needs less computation for UGV location tracking using extended Kalman filtering based on non linear TDoA measurements. To overcome the inaccurate results due to limited linear approximation, this paper suggests a position estimation algorithm based upon an adaptive fading Kalman filter. The adaptive fading factor enables the estimator to change the error covariance according to the real situation. Through the comparison with other analytical methods, simulation results show that the proposed localization method achieves an improved accuracy even with reduced computational efforts.

Adaptive nonlinearity compensation of heterodyne laser interferometer

With its outstanding ultra-precise resolution, the heterodyne laser interferometer systems are commonly used in semiconductor manufacturing industry. However, the periodical nonlinearity error caused from frequency-mixed cross talks limits the accuracy in nanometer scale. In this paper to improve the accuracy of laser interferometer system, we propose an adaptive nonlinearity compensation algorithm using RLS (recursive least square) method. As a reference signal, the capacitance displacement sensor mounted on a linear piezo-electric transducer gives a feedback information on how to transform the elliptical phase into a circular one.

TDOA/AOA localization in RFID system using dual indirect Kalman filter

The time difference of arrival (TDOA) is one of the most accurate localization techniques used in real time locating system (RTLS). However, environmental error and non-line-of-sight (NLOS) error undermine the accuracy of tracking. In order to reduce NLOS error influence, NLOS identification needs to be performed using TDOA standard deviation. After the NLOS identification, we use the additional angle of arrival (AOA) measurements from identified LOS base station. We propose dual indirect Kalman filter (DIKF) which includes error state filter and weight filter to estimate the position of target. The effectiveness of DIKF has been proved by comparing the tracking performance with reference through simulation results.

Laser-Interferometric Broadband Seismometer for Epicenter Location Estimation

In this paper, we suggest a seismic signal measurement system that uses a laser interferometer. The heterodyne laser interferometer is used as a seismometer due to its high accuracy and robustness. Seismic data measured by the laser interferometer is used to analyze crucial earthquake characteristics. To measure P-S time more precisely, the short time Fourier transform and instantaneous frequency estimation methods are applied to the intensity signal (Iy) of the laser interferometer. To estimate the epicenter location, the range difference of arrival algorithm is applied with the P-S time result. The linear matrix equation of the epicenter localization can be derived using P-S time data obtained from more than three observatories. We prove the performance of the proposed algorithm through simulation and experimental results.

Adaptive TLS Approach for Nonlinearity Compensation in Laser Interferometer

The heterodyne laser interferometer has been widely used in linear displacement and precise measurement field. However the periodic nonlinearity that arises from incomplete laser sources and nonideal optical components restricts the precise measurement at the nano-meter level. In this paper, the total least squares (TLS) algorithm which can obtain optimal compensation parameters of nonlinearity is introduced. Using the TLS algorithm, the nonlinearity error is reduced and the measurement data can be more stabilized. The effectiveness of TLS approach is verified through the comparison of the experimental results with those obtained by a capacitance displacement sensor.

Robust Linear Quadratic Sliding-Mode Control for Hard Disk Drives

In this paper, we design a robust servo controller for hard disk drives in track-following mode. To follow the target track center accurately under the effects of system uncertainties and various external disturbances, we propose a robust sliding-mode control with a new switching surface. To reduce the chattering effect, the augmented system adopts two auxiliary states (i.e., state estimates and control input differential), as suggested in this paper. Simulation results show that the chattering effect is reduced with the use of the proposed sliding-mode control to the augmented state system. The performance evaluation with time maximum disturbance shows an improved robustness and stability of the augmented system