A background light resistant TOF range finder with integrated PIN photodiode in 0.35μm CMOS

Time-of-flight (TOF) range sensors acquire distances by means of an optical signal delay measurement. As the signal travels at the speed of light, distance resolutions in the subcentimeters range require a time measurement resolution that is in the picoseconds range. However, typical clock synthesizers and digital buffers possess cycle-to-cycle jitter values of up to hundreds of picoseconds, which can potentially have a noticeable impact on the TOF system performances. In this publication, we investigate the influence of two common types of cycle-to-cycle jitter distributions on the measured distance. This includes a random Gaussian distribution, which is caused by, e.g., stochastic noise sources, and a discrete jitter distribution, which is found when timing constraints fail in synchronous digital designs. It was demonstrated that a Gaussian cycle-to-cycle jitter has only a negligible impact on the performance of the TOF distance sensors up to a standard deviation of 1 ns of the Gaussian jitter distribution. However, even the discrete cycle-to-cycle jitter investigated in its simplest form lowers the distance precision of the TOF sensor by a factor of 2.86, i.e., the standard deviation increases from 2.9 to 8.3 mm.

show abstract

“…3 No background light was present during the measurements, although the pixel has an outstanding background light suppression feature.…”

Section: Measurement Resultsmentioning

confidence: 98%

“…[1][2][3][4] The investigated TOF distance sensors are proven to be very insensitive to background light. [1][2][3][4] The investigated TOF distance sensors are proven to be very insensitive to background light.…”

Section: Introductionmentioning

confidence: 99%

Investigation of the distance error induced by cycle-to-cycle jitter in a correlating time-of-flight distance measurement system

et al. 2014

Self Cite

View full text Add to dashboard Cite

show abstract

“…The reflected optical signal has a power level typically in the nW range. A phototransistor is used to capture the reflected optical signal, as reported in [104], and [105]. The error in distance measurements is from 0.15 mm to 2 mm depending on the amount of background light intensity and on the optical input power.…”

Section: ) Ultrasound Methods Tof Directmentioning

confidence: 99%

“…Triangulation using TOF or AOA derived distances is used in all cases and the scale of the unknown node is also typically in the millimeter range [124], which includes smart dust nodes [123]. Theoretical analysis and experimental results from [31], [124], and [120] indicate that AOA-based optical triangulation has the highest precision at shorter distances, while TOF maintains highest precision at longer distances as shown by [31], [98], [83], and [105]. Optical triangulation (active or passive) and image processing based algorithms for localization [122] continue to deliver the most accurate results in the sub-millimeter to several centimeters range.…”

Section: Power and Accuracy Comparisonmentioning

confidence: 99%

See 1 more Smart Citation

Review and Comparison of Spatial Localization Methods for Low-Power Wireless Sensor Networks

Iliev

Paprotny

2015

IEEE Sensors J.

View full text Add to dashboard Cite

Spatial localization (co-location) of nodes in wireless sensor networks (WSNs) is an active area of research, with many applications in sensing from distributed systems such as micro-aerial vehicles, smart dust sensors, and mobile robotics. This paper provides a comprehensive review and comparison of recent implementations (commercial and academic) of physical measurement techniques used in sensor localization, and of the localization algorithms that apply these measurement techniques. Physical methods for measuring distances and angles between WSN nodes are reviewed, followed by a comprehensive comparison of localization accuracy, applicable ranges, node dimensions, and power consumption of the different implementations. A summary of advantages and disadvantages of each measurement technique is provided along with a comparison of co-localization methods in WSNs across multiple algorithms and distance ranges. A discussion of possible improvements to accuracy, range, and power consumption of selected self-localization methods is included in the concluding discussion. Although the preferred implementation depends on the application, required accuracy, and range, passive optical triangulation is reported as the most energy efficient localization method for low-cost/low-power miniature sensor nodes. It is capable of providing micron-level resolution, however the applicable range (inter-node distance) is limited to single centimeters.1530-437X (c) 2015 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/JSEN.2015.2450742, IEEE Sensors Journal SUBMITTED TO THE IEEE SENSORS JOURNAL 2 on 2.4 GHz radios are: Nordic Semiconductor nRF24L01 transceiver [16] with consumed power from 345 µW to 2.4 mW depending on the refresh rate of the location task, ZigBee Texas Instruments SoC CC2430 radio transceiver [12] with 10 mW to 40 mW consumption depending on implementation, RF Telosb transceivers [17] with consumption from 35 mW to 41 mW depending on the activity profile, and finally on custom radios for IEEE 802.15.4 build from digital ASIC standard cells technology [18] with power consumption of 15.6 mW at 0 dB output power. The communication system is used by a sensor node to perform its message-based self-localization task as well as for broadcasting the basic data collected by the sensor. Communication systems based on ultrasound waves have not been attempted due to the directional dependence of acoustic signals and their dependence on air temperature and humidity. Optical communication between sensors in WSN has been implemented recently using low-power laser diode emitters and detectors [19], modulating Corner-Cube Reflectors (CCR) [20], MEMS CCR arrays [21], MEMS steering mirors (gold coated, refl...

show abstract

Examples of Optoelectronic Integrated Circuits

Zimmermann¹

2018

Silicon Optoelectronic Integrated Circuits

View full text Add to dashboard Cite

A background light resistant TOF range finder with integrated PIN photodiode in 0.35μm CMOS

Cited by 7 publications

References 6 publications

Investigation of the distance error induced by cycle-to-cycle jitter in a correlating time-of-flight distance measurement system

Investigation of the distance error induced by cycle-to-cycle jitter in a correlating time-of-flight distance measurement system

Review and Comparison of Spatial Localization Methods for Low-Power Wireless Sensor Networks

Examples of Optoelectronic Integrated Circuits

Contact Info

Product

Resources

About