Enhanced illumination sensing using multiple harmonics for LED lighting systems

  • Authors:

  • Hongming Yang;Tim C. W. Schenk;Jan W. M. Bergmans;Ashish Pandharipande

  • Affiliations:

  • Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands and Department of Distributed Sensor Systems, Philips Research Eindhoven, Eindhoven, The Nether ...;Department of Distributed Sensor Systems, Philips Research Eindhoven, Eindhoven, The Netherlands;Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands;Department of Distributed Sensor Systems, Philips Research Eindhoven, Eindhoven, The Netherlands

  • Venue:
  • IEEE Transactions on Signal Processing
  • Year:
  • 2010

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Abstract

This paper considers frequency division multiplexing (FDM) based illumination sensing in light emitting diode (LED) lighting systems. The purpose of illumination sensing is to identify the illumination contributions of spatially distributed LEDs at a sensor location, within a limited response time. In the FDM scheme, LEDs render periodical illumination pulse trains at different frequencies with prescribed duty cycles. The problem of interest is to estimate the amplitudes of the individual illumination pulse trains. In our previous work, an estimation approach was proposed using the fundamental frequency component of the sensor signal. The number of LEDs that can be supported by this estimation approach is limited to around 100 LEDs at a response time of 0.1 s. For future LED lighting systems, however, it is desirable to support many more LEDs. To this end, in this paper, we seek to exploit multiple harmonics in the sensor signal.We first derive upper limits on the number of LEDs that can be supported in the presence of frequency offsets and noise. Thereafter, we propose a low complexity successive estimation approach that effectively exploits the multiple harmonics. It is shown that the number of the LEDs can be increased by a factor of at least five, compared to the estimation approach using only the fundamental frequency component, at the same estimation error.