THIS IS HELL

I have nothing new to show, since im still working on the same thing for 2 devposts now. So heres a cool photo

Anyway, after successfully implementing this FFT, I’ll move on to integrate doppler shift as well, like those robots that although have a lidar, still have that internal tracking system. Since lidar drifts, the internal tracking system corrects it. Atleast thats the vision. And implementing doppler shift isnt easy AT ALL, atleast for left to right motion.

im actually tired of failing and trying some solution without using AI.
It would have made it a lot easier but, I’m kinda stupid and egoistic ig?

Made significant progress on FFT implementation

I’m maybe 1/3rd the way to implement FFT ig?
This is getting pretty hard.
I’m spending most of the time just writing, running and testing the code of this implementation.

As it turns out laptops arent really the best at this stuff. And stuff like this being done by actual companies, makes sense now. It’s way too difficult.

Worked more on the implementation of FFT

The picture attached is just when there is forward or backward movement of hand, it glows brighter. Cus I tested with doppler shift a little.

So, I learnt a few more concepts required to make this.

Applied FFT a bit more nicely and neatly.

ALSO I LEARNT COMPLEX FFT WHICH IS AMAZING TBH.

Yea, so far its just applying what I’m learning.

Not easy for a 16 year old to do college shit.

Implemented a basic distance detector using laptop speaker and microphones

Tbh all these difficult concepts, you understand them, do their maths, and then boom, you just implement it using a library. WHY DID I SPEND SO MUCH TIME UNDERSTANDING THEM IN THE FIRST PLACE. I AM A 16 YEAR OLD, ITS REALLY HARD FOR ME TO UNDERSTAND COLLEGE LEVEL SIGNAL PROCESSING, I STILL HAVE FFT AND TO UNDERSTAND!!!! anyway

I’ve been working on a project that basically sees without seeing. So far, i’ve understood concepts like convolution, sampling rate, correlation, stuff to basically find a sound we want from a sample.

I then wrote a code to send out a linear increasing list of frequencies from 10000 to 15000. Then do a convolution of the recieved sound with the target sample to detect where in the recieved sound lies the target sample.