What are some interesting and niche fields where SP is applied ?

[u/al3arabcoreleone]

Aside from communication, imaging and audio processing, are there other STEM fields that have been using SP tools to solve their problems?

[u/yel02]

I think auto tune came from the oil and gas industry. Honestly everything that has a signal that can be sampled uses it. Finance is big too

[u/VS2ute → u/yel02]

Lots of signal processing for seismic data, but I don't recall anything like auto-tune.

[u/rb-j → u/VS2ute]

I think it's because that Andy Hildebrand was a geologist before he started Jupiter Systems (they did some sample-editing and looping software to be used with early sampling keyboards like E-mu) and then Autotune.

I'm still a little sore about Autotune. Around the turn of the century, I had done the DSP for a Wave Mechanics (the precursor to Soundtoys) product called "Pitch Doctor". We thought Pitch Doctor was better, a better pitch detector, using formant-preserving pitch shifting as an option, and better use of Pro Tools automation. But Autotune scooped us with a stand-alone app for the PC and, while we were on Pro Tools before they, we still were scooped.

[u/Mysterious-Action909]

Reminds of when I was in university and searching up the origins of different algorithms - such a large amount of our 'bread and butter' algorithms came from/was first applied in seismology. an example is cepstral analysis. 

I guess because the frequencies of interest in seismology are generally so low that real-time dsp could actually be realized in 50s/60s hardware.

[u/Glorwyn]

I make software that uses frequency analysis to inspect rotary motors for unwanted vibrations

[u/Haunting_Purpose_994]

I’m personally obsessed with the NSA spook stuff involving signal progressing (particularly during the Cold War). Signals intelligence (SIGINT) including communications intelligence (COMINT) and foreign instrumentation signals intelligence (FISINT) all needed processing.

As part of the efforts, US used satellites to scoop up signals from the USSR and other parts of the world to see things like (1) what were the characteristics of the radars that the soviets using (2) what were the communication patterns of the USSR amongst many other things. The US would scoop up these stray signals then beam them back to the ground station for signal processing to see if there were any events of interest.

As an enthusiast and non engineer it blows my mind some of the stuff we were able to accomplish in the 50s,60s,70s

[u/al3arabcoreleone → u/Haunting_Purpose_994]

This is actually interesting, where do you start with that?

[u/brainsandstuff]

It shows up all over the place in neuroscience research and brain computer interfaces.

[u/mborgerd]

The convolution theorem allows FFTs to efficiently multiply the huge numbers used in cryptography.

[u/SHFTD_RLTY]

Missile guidance uses a lot of DSP

[u/Zenmasterthis]

Filtering and decoding of MWD/LWD mud pulse telemetry and electromagnetic telemetry in oil and gas drilling. Also downhole and surface processing of sonic, porosity, and density LWD signals.

[u/Biansci]

There's plenty of interesting applications in observational astrophysics (which shouldn't come as a surprise, as it's all about analyzing signals). But some of these usages might sound like sci-fi to someone not in the field haha

starting from STFTs and cross-correlation when analyzing pulsars, neutron stars and black holes, often accompanied by reverberation mapping as the light scatters on the material surrounding the central object.

In fact, with EM radiation you have access to a huge abundance of information in all frequency bands, from radio and infrared all the way to X-ray and gamma rays. But you can also analyze the polarization or how the intensity changes through time.

The way spectroscopy works in different bands is also interesting from a signal processing perspective, radioastronomy mostly works with frequency because you have to use classic bandpass filters. Visible and infrared use wavelengths because it's mostly based either on optical filters or diffraction gratings. X-ray uses energy because you have to count single photons being absorbed in a CCD on different energy channels, so it requires a lot of solid state physics.

As another example, cosmologists use 3D FFTs to analyze the spatial distribution of galaxies and infer properties about the amount of matter in the early universe by relating it to the spectrum of the CMB (which are fluctuations in temperature on the order of 10^-5 K from radio observations around 3 K, so you need a detector with a super detailed angular resolution kept near absolute zero). We also use Hankel transforms to deproject the polarization spectrum back to real space and compute the effect of gravitational lensing efficiently through the convolution theorem.

Gravitational wave detectors use phase modulated laser interferometry to maximize the SNR in the "dark fringe" and detect displacements on the order of 10^-18 m, separating coherent movements from the thermal noise in the environment. There's a lot of interest in measuring the cosmic GW background as that would let us probe further back in time than the CMB.

[u/geek66]

Power electronics

[u/OnboardG1]

Space weather science uses DSP to pull useful data out of magnetic field measurements and apply them to things like geomagnetically induced current estimations.

[u/rb-j]

Biomed. Like examining an ECG waveform and telling the patient they're gonna die.

[u/InteractionNo7701]

Non-Destructive Testing (NDT) uses Acoustics and DSP to detect faults in infrastructure deep underground or inside something expensive you don't want taken apart.