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dstl / Stone-Soup

A software project to provide the target tracking community with a framework for the development and testing of tracking algorithms.
https://stonesoup.rtfd.io
MIT License
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Getting predicted measurement with no measurement noise #961

Closed narykov closed 1 month ago

narykov commented 4 months ago

It would be useful to have an option to exclude measurement noise when computing statistics of the predicted measurement. In particular, we've been interested to use the predict_measurement method of UnscentedKalmanUpdater when performing measurement linearisation for the IPLF algorithm. However, the unscented transform inside predict_measurement always receives noise covariance, whereas it could have worked without it if covar_noise=None is used, as enabled by this feature in sigma2gauss.

sdhiscocks commented 4 months ago

Look like it shouldn't be difficult to add an additional Boolean argument (noise/measurement_noise/covar_noise??) to all the updaters' predict_measurement method to support this.