Parallax Propeller discriminates Walsh-modulated IREDs

Posted on Sunday, April 7th, 2013 in infrared, LEDs, Parallax Propeller, sensors by the machinegeek

Parallax Propeller guru Phil Pilgrim has posted this IR sensor/discriminator project on the Parallax Propeller forums. “Almost everyone here is aware of the advantages of modulated IREDs for rejection of background IR fluctuations and line-frequency noise from artificial lighting. Typically, the IRED modulation occurs at 38 kHz, to which the integrated detectors are tuned and respond with a digital output. But what if you wanted to respond to more than one IRED at a time and, moreover, know the intensity level of the response from each? Such a question is the theme of this project.

By modulating a set of IREDs, each with a different Walsh function, and using a single analog IR detector, it should be possible to sort out which IREDs the return signal came from, along with how much each one contributed to the response.”

The hardware consists of six IREDs mounted on a Propeller QuickStart board (all available from RadioShack), along with an AMS (TAOS) TSL262R-LF IR to voltage converter.

Read the project details and find schematic and code links on the Parallax Propeller Forum.

This entry was posted on Sunday, April 7th, 2013 at 1:00 pm and is filed under infrared, LEDs, Parallax Propeller, sensors. You can follow any responses to this entry through the RSS 2.0 feed. You can skip to the end and leave a response. Pinging is currently not allowed.

2 Responses to “Parallax Propeller discriminates Walsh-modulated IREDs”

  1. Peter says:

    Interesting concept. I had not heard of Walsh functions before. I was just wondering the advantages of this method over simply scanning the IR emitters serially. Bandwidth, response rate, noise rejection, normalization to neighboring emitters, etc?

    Instead of using Walsh functions for 6 emitters, you could take the period of the Walsh functions, divide by 6 and scan the emitters sequentially with a single pulse. Is the deconvolution fairly simple and computationally light?

  2. Phil Pilgrim says:

    Here’s a link to my original post on the Parallax Forum:


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