Conference Paper

Target Motion Analysis With Bearings And Frequencies Measurements

Thomson-Sintra ASM
DOI: 10.1109/ACSSC.1988.754037 Conference: Signals, Systems and Computers, 1988. Twenty-Second Asilomar Conference on, Volume: 1
Source: IEEE Xplore


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    • "Extra information can be prior information, for example a given velocity or a given heading. Another way is to consider jointly other measurements such as frequency measurements; this supposes that the source emits pure single tones and makes necessary a dedicated processing [6]. We can sometimes benefit from bearing measurements collected by another sensor, if the target is detected by both platforms and if the respective bearing tracks are properly associated [7]. "
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    ABSTRACT: This paper addresses the problem of bearings-only target motion analysis) of a maneuvering source, whose trajectory is composed by two legs at constant velocity. Under very large assumptions, the target trajectory is proved observable from a non-maneuvering platform. Two cases are considered: first, the time of the target maneuver (t<sub>M</sub>) is perfectly known. Secondly, t<sub>M</sub> is unknown. In both cases, a batch estimator is proposed and its performance is compared with the classic cramer-rao lower bound (CRLB). Monte-Carlo simulations reveal the efficiency of the estimator.
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    ABSTRACT: Estimating position and velocity of a moving source requires at least an ownship maneuver when performing bearing-only tracking (BOT). By concurrently processing bearing and Dopplerized radiated frequencies a unique target motion analysis (TMA) solution is available without any maneuver. A simple, fast, non-time-recursive estimator, working on several unknown measured spectral lines, is presented. The statistical efficiency of such a Doppler and bearing tracking (DBT) is proved by computer simulation. Simulation results show that DBT can yield proper estimates of source trajectory: range accuracy better than 10% within at most 10 min for a source at 20 km and nine sinusoids
    Acoustics, Speech, and Signal Processing, 1989. ICASSP-89., 1989 International Conference on; 06/1989
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    ABSTRACT: A Newton-type method is used to solve the target motion analysis (TMA) problem with respect to bearing and frequency measurements from a passive sonar system. In many long-range sonar situations the TMA problem is ill conditioned and suffers from a small signal-to-noise ratio. Although Kalman filters have been investigated extensively it is known that maximum likelihood (ML) estimation is superior in these cases. The main reason for the good performance of the ML method is that the underlying numerical optimization problem deals with the ill conditioning of the problem. This work illustrates how the conditioning depends on the geometry of the tracks and the signal-to-noise ratio. Monte Carlo simulations with respect to the measurement noise show the influence on the ML estimation performance for three specific cases concerning multileg situations and bottom bounce measurements
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