방위각과 다중주파수 정보를 이용한 표적기동분석(MFTMA) 성능 개선 연구
- 방위각과 다중주파수 정보를 이용한 표적기동분석(MFTMA) 성능 개선 연구
- Other Titles
- A Study Of TMA Performance Improvement with Bearing and Multi-frequency Measurements
- Alternative Author(s)
- Kim, Woo Chan
- Issue Date
- Target Motion Analysis (TMA) is the target state estimation using passive SONAR systems which measure bearing information only. TMA is a one of the most important technique for underwater combat systems.
Bearing only TMA (BTMA) needs observer maneuvers to guarantee observability. For bearing and Doppler frequency TMA (FTMA), however, the observer maneuver is not a prerequisite. Since observer is allowed to have a constant velocity in the FTMA environment, a line arranged sensor such as the Towed Array SONAR System (TASS) measures angle information better. Moreover, bearing and multi-frequency TMA (MFTMA) has better estimation performance than FTMA.
TMA can be divided to two parts
batch estimation and sequential estimation. Batch estimation cumulates measurements during W interval and calculates appropriate solution using batch of measurements. On the other hand, sequential estimation evaluates target state using measurement at each scan sequentially. Batch estimation performs stable estimation performance but it has a restricted assumption on dynamic model and it is not real-time applicable problem. Sequential estimation is more adaptive for real-time applications and maneuvering target cases but it needs a proper initial estimation of target state.
In this paper, we propose that batch estimation is used for estimation of initial target state for the sequential estimation. The MFTMA system model equation is presented in Section II. Section III presents Searching Algorithm and MLE batch estimation. Sequential estimation algorithms are presented in Section IV. For improved robustness of the MFTMA, a series structure under a fading measurement environment is presents in Section V. Section VI presents a new support algorithm for batch estimation. It can be need to estimate proper intervals for data accumulation for the batch estimation algorithm.
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- GRADUATE SCHOOL[S](대학원) > ELECTRONIC,ELECTRICAL,CONTROL & INSTRUMENTATION ENGINEERING(전자전기제어계측공학과) > Theses (Master)
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