Exercise: Radar is widely applied in robotics such that a mobile robot can
sense the environment. For radar detection problem as (3.29) and (3.30), suppose
$\|s\|^2 = 100$ and $n \sim G(0,1)$. With $P_{FA} \leq 10^{-2}$, please design the radar detection
mechanism.
Remark: Radar detection has to acquire reflected waveform, which usually involves
some unknown parameter(s), and thus composite hypothesis can be applied in radar
detection together. As a matter of fact, Neyman-Pearson criterion was developed in
early days of statistics as an intuitive approach, which plays an important role in
many hypothesis testing or classification problems in machine learning.