Performance bounds for joint estimation of ionospheric and target parameters in MIMO-OTH radar

Ionospheric information is required when estimating target parameters in skywave over-the-horizon (OTH) radar. Unlike the traditional OTH radar which uses only the measurements of ionospheric parameters obtained from an ionosonde to estimate the target parameters, the multiple-input multiple-output skywave OTH (MIMO-OTH) radar studied in this paper estimates the ionospheric and target parameters jointly by exploiting the data received by both the ionosonde and the radar receivers. Two scenarios where the prior distribution of the ionospheric parameters is either known or unknown are considered. For the case when ionospheric parameter prior distribution is unknown, the joint maximum likelihood (JML) estimator is investigated and the Cramér-Rao bound (CRB) is derived. For the case when the ionospheric parameter prior distribution is known, the hybrid maximum likelihood and the maximum a posteriori (ML/MAP) estimator is studied and the hybrid Cramér-Rao bound (HCRB) is developed.

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Performance bounds for joint estimation of ionospheric and target parameters in MIMO-OTH radar

Semantic Scholar · Engineering · 2014

Abstract

Ionospheric information is required when estimating target parameters in skywave over-the-horizon (OTH) radar. Unlike the traditional OTH radar which uses only the measurements of ionospheric parameters obtained from an ionosonde to estimate the target parameters, the multiple-input multiple-output skywave OTH (MIMO-OTH) radar studied in this paper estimates the ionospheric and target parameters jointly by exploiting the data received by both the ionosonde and the radar receivers. Two scenarios where the prior distribution of the ionospheric parameters is either known or unknown are considered. For the case when ionospheric parameter prior distribution is unknown, the joint maximum likelihood (JML) estimator is investigated and the Cramér-Rao bound (CRB) is derived. For the case when the ionospheric parameter prior distribution is known, the hybrid maximum likelihood and the maximum a posteriori (ML/MAP) estimator is studied and the hybrid Cramér-Rao bound (HCRB) is developed.

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