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- W2790596485 abstract "The PMHT and the H-PMHT algorithms reviewed in Chaps. 3 and 4 both assume that the source of each point measurement is an independent draw from a probability mass function.The individual component probability masses are denoted (pi _t^m) and are hyperparameters of the measurement function. When these hyperparameters are unknown they are estimated using a weighted relative frequency. This limits the dynamics of (pi _t^m): it must be either time independent or constant. As described in Chap. 5, these assignment prior estimates can be a useful metric for track management because they specify how much influence a particular track has over the frame at time (t). However, if the target amplitude fluctuates then the estimates of the prior will be pelagic. Figure 6.1 shows two examples of a fluctuating target following a Swerling II model (Skolnik, Introduction to radar systems, McGraw-Hill, New York, 2001, [7]). The plots show the instantaneous amplitude of the target and the mixing proportion estimate (hat{pi }_t^m) resulting from applying H-PMHT to images with this target. Two different average SNRs are shown. For a 10 dB SNR, the estimated mixing proportion (hat{pi }_t^m) is so highly correlated with the instantaneous amplitude that it is hard to pick them apart. Even for the 0 dB average SNR, there is a high degree of correlation: the estimate follows the target fluctuations very closely. This would be desirable if the aim was to characterise the temporal variations but the SNR, in this case, has a stationary statistical distribution, a better characterisation would be to estimate the mean or another appropriate sufficient statistic. An alternative perspective is to treat the instantaneous SNR as a noisy time series. The underlying signal component is contained in the low-frequency part of the spectrum and the higher frequencies are noise." @default.
- W2790596485 created "2018-03-29" @default.
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- W2790596485 date "2018-01-01" @default.
- W2790596485 modified "2023-09-25" @default.
- W2790596485 title "Poisson Scattering Field" @default.
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- W2790596485 doi "https://doi.org/10.1007/978-981-10-7593-3_6" @default.
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