Not an average software engineer--beautiful page (imperfect spelling)!
Why does detection scale as the 4th root of the RCS? Nice problem for the radiation theory part of a graduate electrodynamics class.
> Why does detection scale as the 4th root of the RCS?<p>Because the power returned to the antenna scales as the -4th power of the distance to the target, and detection depends on that power being greater than some threshold. If the fourth power (rather than the square) is surprising, think of the reflection as re-transmitting the power that arrived at the target. The incident power on the target goes as RCS/r^2, and the power that makes it back to the original antenna gets another factor of 1/r^2, so the return scales as RCS/r^4.
It's a 4th power because you're doing the inverse square law twice, once for the outbound pulse and once for the reflection.
Thanks. I needed that reminder to sometimes NOT just solve a matrix of 3000 * 3000 equations and merely make an assumption and take an integral, metaphorically.
The instant I realize it's an LLM generated piece. I'm out. Thanks for adding all the animations to make it abundantly obvious.
What animations ?
the footer says "made by hand, mostly." not sure what that means, though!
"All visualizations were drawn/generated by me and code can be found in this project's github repo"<p>Also, I feel it's not who the generator is that should concern you--it's the quality of the text.<p>I would much rather read something that is clear, concise, and consistent regardless of the source.
>where RR is the distance from the target (imagine the radar being very far away) en.wikipedia.org . This formula might look intimidating, so let's break it down:<p>You didn't even read your own slop. Why should anybody else?
A random professor's academic website is usually barebones, no CSS, only HTML, mostly text. But the value one finds there is incredible.<p>As opposed to this, vibe coded slop which neither explains the stuff that's already there, nor is pedagogical. Why use AI for this?