Monday, October 16, 2006

Making A Human Tracker

Students are eager to build a human tracker system in the campus. They want each person to carry a transmitter wherever s/he goes. Multiple towers will receive their signals and convey this reception to the central computer. The computer will time the arrivals with GPS unit, and locate the emitter by simple triangulation. The computer can track the location on a map for an easy display.

Students wanted to know if this was feasible. They had ideas of using high-freq dishes, radio-id tags, etc. However, I suggested them to build a system at low frequencies, which will be less prone to blockage. This is of concern, since the system will otherwise fail if the person reaches in a classroom.

We are not sure about how much of signal is needed to make it detectable at the receiving stations, but we are initially going to play with a system working over less than 300 mtrs, using simple yaggi antennas.

Monday, October 09, 2006

Teaching listless lists...

How Does One Teach Totally Disconnected Students?

I am about to teach my students something about linked lists, a fascinating topic thanks to
Donald Knuth's book ("The Art of Computer Programming"). It is apparently an unfinished book, Knuth keeps updating it all the while, Ramprasad tells me. Would my students read it? Anyway, I just finished the logic behind the linked lists, stackes, queues, and deques ('decks' as they are called). Here is what is stuck in my foggy brain:
  1. One tries to process data inside the computer, most likely it is some kind of a data table.
  2. Not only the data, but the interconnection between various elements are of importance, we process the information related to these inter-relationships.
  3. For example, a 1-dimensional array of data could be sorted or searched...
  4. The data could also be a 2-D image, or some higher dimensional object. Or it could have a tree-like structure, or even more complex...
  5. So, a linked list representing all the data is the most general type: stacks, queues, deques.
  6. Ah, and lastly, I learnt to pronounced 'deque' correctly (it is like 'deck', dummy!)

There are some gory details of malloc/calloc that I have been reading, oh well. I will use them and then write more about them...

Friday, October 06, 2006

Making an Amateur Radio Telescope

Radio Interferrometer

Today I detailed the entire telescope project with Anita. The standard components will be:
  1. Two antennas, separated by about 100 meters. To begin with, of course, we will start with one antenna. Signal frequency of 40/60 MHz +- 5 MHz
  2. Pre-amplifier will be required in at least one case, to boost the signal by 20 dB and carry it over 100 meters. Signal freq 40/60 MHz +- 5 MHz.
  3. RF to IF conversion followed by an appropriate filter: 0-2 MHz band chosen.
  4. IF amplification, possibly two amplifiers back to back for 40 dB or so gain: signal freq. 0-2 MHz.
  5. Phase shifter and adder (with 90 degrees phase difference), followed by a detector. The output is a amplitude time series at the rate of 1/16 second.
This kind of project requires a team of students, possibly 8 students working on different aspects simultaneously. Complex job, but it will be fun if we invest their time in it...

Images and Fourier Analysis

We want to teach students to understand the concept of Fourier spectrum and its usage in image processing using Octave. Though students know formulae, they have no physical understanding of Fourier domain and how to use coefficient to gain something useful from an image or signal. We have simple programs to clarify some fundamental ideas about Fourier domain.

I created programs for their use:
  1. Simple routines to create images with sinusoidal waves. They should understand the concept of 'spatial waves' and 'spatial frequencies'.

  2. Then students are asked to look at a simple circular step function in an image and its Fourier Transform (Sinc function plotted using SQRT). They are expected to vary the amplitude and size of the step function in the image and understand the correspondence with the Sinc function in the Fourier spectrum.

  3. Students are then given two Gaussians of different widths, with some separation. One can now use Fourier filters to smooth the image. As one throws away 'higher spatial frequencies', one would see some details lost. How much of smoothing leads to which details being lost?
  4. Finally, we use a textbook image to grasp the idea that different 'structures' in an image are nothing but grey-level variations of certain spatial sizes. These sizes correspond to 'spatial wavelengths'.