• 전자공학회논문지
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• 제52권9호
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• pp.125-131
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• 2015

함정용 전자광학추적장비의 종속추적 표적지향 성능 개선을 위해 칼만 필터를 제안하였다. 전자광학추적장비의 추적기능 수행 시 표적지향 성능 저하의 주요 요인인 전송 지연 및 측정 오차를 칼만 필터를 활용할 경우 최소화할 수 있는 장점이 있다. 칼만 필터를 활용하여 방위각, 고각 방향으로의 표적지향 오차가 감쇄됨을 확인하고 전자광학추적장비에 적용해봄으로써 전자광학장비에서 빈번하게 발생하는 표적 추적 오차 개선 시스템으로 적합성을 제시하였다.

• Journal of Positioning, Navigation, and Timing
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• 제12권3호
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• pp.271-280
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• 2023

Pedestrian Dead Reckoning (PDR) methods using initial sensors are being studied to provide the location information of smart device users in indoor environments where satellite signals are not available. PDR can continuously estimate the location of a pedestrian regardless of the walking environment, but has the disadvantage of accumulating errors over time. Unlike this, WiFi signal-based wireless positioning technology does not accumulate errors over time, but can provide positioning information only where infrastructure is installed. It also shows different positioning performance depending on the environment. In this paper, an integrated positioning technology integrating two positioning techniques with different error characteristics is proposed. A technique for correcting the error of PDR was designed by using the location information obtained through WiFi Measurement-based fingerprinting as the measurement of Extended Kalman Filte (EKF). Here, a technique is used to variably calculate the error covariance of the filter measurements using the WiFi Fingerprinting DB and apply it to the filter. The performance of the proposed positioning technology is verified through an experiment. The error characteristics of the PDR and WiFi Fingerprinting techniques are analyzed through the experimental results. In addition, it is confirmed that the PDR error is effectively compensated by adaptively utilizing the WiFi signal to the environment through the EKF to which the adaptive error covariance proposed in this paper is applied.