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Object Sensing using 802.11ad devices

Object Sensing using 802.11ad devices. Date: 2010-09-15. Authors:. Abstract. The hardware of an 802.11ad device is very similar to that of a powerful short-range radar could be used to sense objects in local vicinity of device estimate position and movement of objects

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Object Sensing using 802.11ad devices

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  1. Object Sensing using 802.11ad devices Date: 2010-09-15 Authors: Thomas Derham, Orange Labs

  2. Abstract • The hardware of an 802.11ad device is very similar to that ofa powerful short-range radar • could be used to sense objects in local vicinity of device • estimate position and movement of objects • A “dual-mode” device (communications + object sensing) wouldmake for a low-cost implementation with various applications • smart home/environment, security sensing, … • collision avoidance, emergency detection of humans, … • coexistence with 11ad communications can be ensured • schedule self-allocated SPs for object sensing to prevent interference • efficient method to minimize effect on network efficiency Thomas Derham, Orange Labs

  3. Using 802.11ad device as a radar • Merits: • Baseband bandwidth: 2 GHz => range resolution: 7.5 cm • Array antenna beamwidth: 23 deg (6x6) => angular resolution: 0.8 m @ 2m range • High Doppler / micro-Doppler sensitivity due to small wavelength (5 mm) • Demerits: • limited dynamic range (ADC/DAC ENOB) - may need tight AGC control • fast Tx/Rx antenna switch may be required in case of shared antenna Thomas Derham, Orange Labs

  4. Basic operation • Pulse Doppler radar: • (1) Tx generates and transmits pre-defined radar pulses at pre-defined times • (2) Rx coherently receives reflections of these pulses from nearby objects • (3) Joint signal processing of all received pulses • (4) Repeat for different antenna beam directions to form 4D radar image • range, azimuth, elevation, radial velocity Thomas Derham, Orange Labs

  5. Information in Radar Image • Radar image is 4D array of effective complex reflectivity values • Dimensions: range, azimuth, elevation, radial velocity • From radar image, presence of objects can be detected • Position estimation • range, azimuth, elevation • Movement estimation • linear radial velocity • from conventional Doppler effect – linear movement gives rise to single “spike” in velocity dimension • vibration frequency • from Micro-Doppler effect – vibration causes series of “spikes” in velocity dimension (Bessel weighted), spaced by the vibration frequency Thomas Derham, Orange Labs

  6. Applications • Example capabilities • create 3D image of objects in vicinity • estimate distance to nearest object (e.g. on current trajectory) • identify presence of human in vicinity (breathing / heart beat micro-Doppler) • identify activity of human e.g. waving arms (micro-Doppler gait analysis) • Example applications (opportunistic or non-opportunistic) • Smart Environment • determine and predict location of individual, … • Vehicle/robot collision avoidance • Security sensing • Emergency detection of humans in earthquake (battery backup) Thomas Derham, Orange Labs

  7. Structure of transmission/reception bursts of pulses – objects are approximately static over each burst if Tx/Rx antenna switch • pulse length: • pulse transmission must (or preferably should) finish before receiver activates • receiver active time: • pulse length + max. propagation time • Burst Repetition Interval: • Nyquist requirement according to max. Doppler frequency • total observation time: • according to required Doppler resolution Thomas Derham, Orange Labs

  8. Structure of transmission/reception (2) bursts at each beam angle are interleaved in time • integration gain: • according to required SNR for radar image • 3 inequalities for required structure: • number of pulses per burst: • number of bursts: Thomas Derham, Orange Labs

  9. Transmitted waveform • transmitted pulse is generally short • spectrum of pulse should be well controlled to: • obtain low range-domain sidelobes • meet spectral mask requirements • e.g. classical chirp (linear FM) waveform • raised cosine time-domain window • range resolution approx. 10 cm • with B = 2 GHz, Thomas Derham, Orange Labs

  10. Signal processing • (1) pulse integration • coherent summation of received pulses in one burst • (2) matched filter • cross-correlation with reference Tx waveform => range profile • (3) Doppler processing • form array comprising values from each range bin (sample of range profile) over all bursts • FFT to form Doppler profile for each range bin • note: phase noise strongly mitigated if common Local Oscillator used forTx and Rx due to “range correlation effect” • (4) combine over all beam directions to form 4D radar image • (5) object detection/classification/identification Thomas Derham, Orange Labs

  11. Coexistence with 11ad communications • device can request self-allocated SPs for object sensing • length and spacing according to the timing of bursts • e.g. using service period requests (SPR) • however, in 11ad cannot request position of SP within a BI • results in irregular time-domain sampling of Doppler • requires interpolation/resampling (sensitive to noise) • therefore, it is preferable that object sensing device is also PCP • can first schedule its own SPs wherever it wants Thomas Derham, Orange Labs

  12. Practical example • min/max range: 3 / 10 m • max Doppler freq: 2 Hz; Doppler resolution: 0.05 Hz (for rapid breathing sensing) • SNR of radar image: 20 dB (at max range) • separate Tx/Rx antennas (no switch required) • pulse length: 20 ns • BRI: 0.25 s • Pulses per burst: 1 • Burst length: 87 ns • Number of bursts: 80 • Total observation time: 20 s • if interleave total of 100 different beam angles, need 87 us SP every 0.25 s • channel overhead for sensing over 20 s period: 0.035% Thomas Derham, Orange Labs

  13. Conclusions • Object sensing capability in 802.11ad devices could provide: • differentiating features (reuse powerful 11ad device hardware) • new potential ecosystem of applications to make 11ad devices even more compelling! • potentially increase market acceptance! • Low implementation complexity • fixed transmitted radar waveforms • DSP may share some logic (e.g. DFT core) with OFDM modulator, … • Coexistence with 11ad communications • efficient use of self-allocated SPs prevent interference within PBSS and minimizes effect on network performance Thomas Derham, Orange Labs

  14. References • [1] B. Lyonnet et al, “Human gait classification using Micro-Doppler time-frequency signal representations”, IEEE Radar Conference 2010 • [2] D. Cook, “Smart Environments: Technology, Protocols and Applications”, Wiley 2004 • [3] IEEE P802.11ad draft amendment D0.1, 2010 • [4] M. Budge, “Range Correlation Effects on Phase and Amplitude Noise”, Southeastcon, 1993 Thomas Derham, Orange Labs

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