Scatterer Model Assisted Altitude Estimation in FDA Radar

In meter-wave radar altitude measurement, inad-equate ground absorption easily leads to significant multipath effects. Traditional processing methodologies, when deployed without considering the implications of multipath phenomena, often incur substantial performance degradation. To mitigate these issues, this study employs the scatterer model, a technique widely utilized in object localization, to effectively counteract multipath distortions. It is worth noting that the scatterer model, typically reliant on the presence of at least two targets or scatter-ers-or known positions of a solitary target or scatterer-faces implementation challenges within radar systems due to these stringent prerequisites. To bridge this gap, we utilize Frequency-Diverse Array (FDA) radar for the initial estimation of path delays and angles, followed by a refinement step employing the scatter model. We integrated insights from previous literature on the scatterer model to devise a non-iterative target altitude estimation algorithm. This algorithm is based on the Best Linear Unbiased Estimator and is combined with FDA radar, by using he angles of arrival (AOA) and time differences of arrival (TDOA) to achieve efficient altitude estimation without iterative processes. This validation underscores the feasibility of integrating FDA radar in conjunction with scatterer models to circumvent the limitations of traditional radar processing in altitude estimation.