Kyunghyun Lee

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.

TDOA/AOA based geolocation using Newton method under NLOS environment

Geolocation of a mobile is a significant problem in many industrial fields. Among many schemes of geolocation, Time Difference of Arrival (TDOA) and Angle of Arrival (AOA) are widely used for estimation of a mobile location in past few years. In both TDOA and AOA based geolocation, there are two kinds of factors which deteriorate the accuracy of location estimation: Nonline-of-Sight (NLOS) noise and measurement noise. In this paper, Kalman filter based hypothesis test is applied for eliminating NLOS noise contained measurement data. Also, the measurement noise can be compensated through Newton method based optimization scheme using the identified LOS measurement data. Through the proposed hybrid algorithm, the optimized solution of which the estimation error is minimized can be acquired. Simulation results confirm the performance of our proposed scheme.

Neural Network-Based Laser Interferometer Compensation for Seismic Signal Detection

We propose a seismic wave detection method in the frequency domain using a heterodyne laser interferometer, which is used in ultraprecision fields as a displacement measurement device. In seismology, it is important to accurately measure seismic waves. To overcome the limited frequency range and low resolution of accelerometers and velocimeters and to enhance the precision of seismic data analysis, we use the heterodyne laser interferometer as a seismic detection apparatus. We apply the data fusion algorithm with the adaptive standard deviation ratio ( ) derived from the neural network to improve the laser interferometer’s measurement precision. Moreover, by using the interferometric characteristics, we analyze the seismic data in the frequency domain. To determine the location of the epicenter from the body wave propagation analysis, we apply the STA/LTA algorithm to the measurement data. The effectiveness of the proposed laser interferometric seismometer is shown through experiments to locate the precise epicenter.

Closed-Form Solution of TDOA-Based Geolocation and Tracking: A Recursive Weighted Least Square Approach

The location determination technique using time difference of arrival (TDOA) measurements has been widely used in the military and observation industry. The accuracy of geolocation estimation is a very significant problem because measurement data are affected by environmental noise. Environmental noise occurs due to measurement error and the non-line of sight (NLOS) problem. This paper presents a Kalman filter-based NLOS section identification method and an iterative estimation of emitter location using the recursive weighted least square (RWLS) algorithm. Using fixed receivers with known locations, we obtain TDOA data that contain environmental noise. We identify the NLOS section of each receiver using a Kalman filter. Using the identified line of sight (LOS) TDOA measurements, we accurately derive the estimated location of an emitter with a fast calculation speed using the proposed RWLS algorithm when we receive additional TDOA data. In order to confirm the performance of the RWLS algorithm, the presented simulation results show that the proposed technique achieves improved accuracy and speed for estimating the emitter location.

Earthquake magnitude estimation using Recursive Least Squares

Heterodyne laser interferometer, which is used as a sensor for high-precision displacement measurement, is used to measure the ground motion and seismic waves as a seismometer. Through the displacement variation obtained by the precision measurement, we predict the magnitude of the earthquake. The Recursive Least Square (RLS) method reduces the error of earthquake magnitude prediction. RLS method is to update the relation between the magnitude and Pd adaptively to predict the magnitude of earthquake more accurately. With the simulation results, we reduced error factors and improved the accuracy of earthquake magnitude estimation.

TDOA AOA Hybrid Position Estimate Solution using Newton Method

The position determination method has been used widely in location based industry. Precise determination of a mobile position is one of the significant problems in geolocation. Among geolocation techniques, both time difference of arrival (TDOA) and angle of arrival (AOA) are the most widely used methods for estimation of mobile position. In this paper, TDOA/AOA hybrid position estimation formula is proposed to express a mobile position. This hybrid scheme improves the estimation performance by increasing reliable measurement data set. Also, we suggest Newton method based optimization algorithm to obtain a solution that minimizes determination error. Some simulations confirm that the proposed Newton method based optimization algorithm improves the accuracy for acquiring a mobile position estimate. Keywords— position estimation, time difference of arrival, angle of arrival, Newton method, optimization, measurement error compensation.