Advancements in Chree's Method for Enhanced Signal Amplitude Estimation in Remote Sensing Applications

Chree's method of superimposed epochs analysis effectively estimates signal amplitude, making it useful for identifying extreme states of a target, even with non-sinusoidal or aperiodic signals. In remote sensing radar applications, as an example, this method can reveal the maximum and minimum observed Radar Cross Section (RCS) as the radar moves around or the target rotates. Evaluating signal amplitude with Chree's method requires an initial hypothesis about the signal's period length. Typically, a series of discrete period length hypotheses are tested using a standard null test to maintain a constant false alarm rate. However, automating this process poses a challenge because the actual period length often falls between hypothesized values, causing phase walk-where a phase shift occurs with each hypothesized periodic cycle-leading to incoherent signal addition and signal loss over time. To address this, we developed an algorithm that effectively tests between discrete period length hypotheses by applying a phase shift that counteracts a phase walk, maintaining a constant false alarm rate, and enabling the processing of jointly synchronized signals. These advancements facilitate the fusion of signals from different sensor types, such as radar and electro-optical/infrared, thereby enhancing target analysis. This paper details these innovations and demonstrates their performance benefits.