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RADIO INTERFEROMETRIC GEOLOCATION

RADIO INTERFEROMETRIC GEOLOCATION. Will Hedgecock EECE 354. 11/08/2010.

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RADIO INTERFEROMETRIC GEOLOCATION

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  1. RADIO INTERFEROMETRIC GEOLOCATION Will Hedgecock EECE 354 11/08/2010 M. Maroti, B. Kusy, G.. Balogh, P. Volgyesi, A. Nadas, K. Molnar, S. Dora, A. Ledeczi. "Radio Interferometric Geolocation". in Proc. ACM 3rd Conference on Embedded Networked Sensor Systems (SenSys'05), November, 2005.

  2. Motivation • Many WSN (Wireless Sensor Network) applications require knowledge of the location of individual nodes in the system • Existing localization techniques have limited range and accuracy • Usually acoustic-based • Also true of signal strength methods with accuracies of up to a few meters • Tradeoff between range and accuracy • Difficult to provide stealthy operation modes in traditional approaches • Requires ultrasound • Most existing techniques work only in 2D

  3. Radio Interferometric Positioning System (RIPS)

  4. Background • Traditional radio interferometry is used in physics, geodesy, and astronomy to measure relative distances to objects • Works by measuring a single signal from two separate directional antennae and performing cross-correlation • Resulting signal interference can be used to determine distance to an object, the precise relative location of the two receiving antennae, or, if the locations of the two receivers are known, the precise location of the radio source • Standard Radio Interferometric systems are quite expensive and not conducive to WSN applications

  5. General RIPS Overview • Directly generate an interference signal using two transmitters at high frequencies • If the transmitters are signaling using slightly different carrier frequencies, the resulting interference signal will have a low-frequency envelope • Can therefore be measured by cheap, low-precision hardware • The phase offset of the interference signal at the receivers corresponds to the relative positions of the four nodes in the system • Thus, with at least 8 nodes, we can calculate the relative location of all of the nodes in 3D

  6. General RIPS Overview

  7. RIPS Key Points • The phase offset of a low-frequency signal is measured (cheaply), but it corresponds to the wavelength of a high-frequency carrier signal • This allows low-precision techniques carried out on resource-constrained WSN nodes to produce highly accurate results • Absolutephase offset depends on several factors including exact time instances when signal transmissions were started, BUT relativephases measured by the receivers depends only the distances between the transmitters and receivers and the carrier frequency • By measuring the phase offsets at different carrier frequencies, we can infer the relative positions of the nodes

  8. Radio Interferometric Properties • This theorem forms the basis for using phase offsets from a low-frequency envelope to obtain highly accurate results

  9. Radio Interferometric Properties

  10. Radio Interferometric Properties

  11. Radio Interferometric Properties

  12. Radio Interferometric Properties

  13. Sources of Error • Carrier Frequency Inaccuracy: • Carrier Drift and Phase Noise: All previous theorems operate under the assumption of completely stable signals • Any frequency drift will be directly observable in the relative phase offsets at the receivers • Minimizableby making each phase measurement as short as possible • Phase noise (transients, shocks, etc.) is more serious • Multipath Effects • RSSI measurement delay jitter (in circuitry): not noticeable in measurements • Signal-to-noise ratio: dependent mainly on distances between nodes • Signal processing error: well-studied and there exist good approximations/models to deal with this • Time synchronization error: Assuming 2kHz interference frequency and 2us synch accuracy, this generates a 0.4%*2πphase offset error

  14. RIPS Implementation

  15. RIPS Implementation • Base Station: • Handles scheduling of transmitting pairs, frequency calibration, calculation of the Dabcd range, and actual localization • Motes: • Handles CC1000 radio chip pure sine wave transmission drivers • Synchronizes participating nodes • Handles transmission/reception of signals • Estimates the frequency and phase offset of the sampled RSSI signal

  16. Radio Characteristics • Configured to transmit in the 433MHz frequency band • Capable of transmitting an unmodulated sine wave in a wide frequency band (400-460MHz) • Necessary for calculating the actual range from the phase offset differences • Ability to tune transmitter with high granularity (65Hz steps) • Necessary to achieve separation of the two transmitters • Short-term frequency stability of transmitter • Precise capture of RSSI with small delay jitter • Capable of transmitting at different power levels • Necessary because transmitter/receiver distances can vary to the point that a closer transmitter completely overwhelms the signal from the more distant one

  17. Time Synchronization • No network-wide synchronization • Only the nodes participating in the current ranging round are synchronized and only for one measurement • A master node sends a synch message containing its local absolute timestamp and timestamp in the near future indicating when measurements should begin • All receiving nodes convert the measurement time to their local time, set up a start timer, and retransmit the message • In this way, nodes outside the initial receiving range can take part in the ranging round • It was shown that all errors combined in this protocol still allow for microsecond synchronization accuracy of the nodes • To account for circuitry jitter, all received messages are immediately timestamped before being passed to the ADC and other measurement circuitry • Phase offset can then be found relative to the actual receive time without jitter

  18. Time Synchronization

  19. Radio Tuning and Calibration • Calibration is necessary to take into account temperature and voltage effects on carrier frequency • Can take up to 34ms and should be performed every time the frequency changes by more than 1MHz • Frequency span is separated into calibration channels with channel 0 being 430.1 MHz, and each separation being 0.526 MHz apart • Within each channel, fine-grained tuning can be performed in 65Hz intervals without requiring recalibration (very fast) • Nominal tuning frequency, f, obtained from formula: • One limitation is that actual tuning can differ from nominal f by up to 2kHz • Due to measurement time constraints (29ms) and mote sampling rates (9kHz), transmission frequencies must differ in the range 200-800 Hz

  20. Tuning Algorithm • 1 transmitter begins transmitting at nominal f, while second transmitter begins transmitting at where i = -15, -14, ... 15 • A receiver node analyzes the interference signal and determines which i creates an interference frequency closest to 0 • It transmits this back to one of the transmitters which adjusts its transmission frequency • It has been noted that these inaccuracies are mainly due to imprecisions in the crystal driving the node • Thus, tuning factors are not constant between different channels on different nodes, but: • Tuning factors are fairly linear across different channels of the same node • Tuning factors can be found for two different channels of a node and interpolated to correct tuning factors for other channels

  21. Frequency and Phase Estimation • Performed on each mote then transmitted to the base station along with a quality indicator value • 256 samples per measurement • Very resource-constrained (only about 820 CPU cycles per sample for online processing) • Post-processing a bit more relaxed (about 10000 CPU cycles available) • No floating point hardware, so computationally expensive solutions, such as Fourier analysis, are not feasible

  22. Frequency and Phase Estimation

  23. Online Processing • Peak detection performed online by the ADC ISR • Raw samples are filtered by a moving average to smooth results and enhance SNR • Min/max values are acquired from the leading 24 samples (must contain at least one full period) • The acquired amplitude value serves as a quality indicator of the measurement • Samples above a threshold of 20% of the max amplitude measured are identified as high amplitude samples • Peaks are defined as center points of 2 consecutive high-threshold crossings (not-high to high, then high to not-high) • Peaks are discarded if the signal has not crossed the low threshold since the last peak to minimize false positives

  24. Post Processing • Works exclusively on peaks identified and stored in the online algorithm • Determines the shortest period between subsequent peaks • Accumulates the sum of all periods that are not longer than 130% the length of the shortest period • Frequency is defined as the reciprocal of the average of this sum • Phase is defined as the average phase of accepted peaks • Small frequency errors can result in large phase errors, so phases are computed relative to the center of the sample buffer thereby reducing accumulated phase error • The estimated frequency, phase, and amplitude tuple is sent to the base station

  25. Scheduling • Two levels: • 1) High-level scheduling for selecting the pair of transmitters • Should minimize the required number of interference measurements while producing enough to localize in 3D • 2) Low-level scheduling for coordinating the activities of the transmitters and receivers • Includes time synchronization, frequency calibration, and transmission power scheduling • full/full power, full/half power, and half/full power all carried out by each transmission pair • Currently 13 channels 5MHz apart are used between 400-460MHz

  26. Range Calculation • With enough measurements at different frequencies, we can solve for dABCD • Possibility of multiple solutions differing by small integer multiples of the wavelength • Define error function: • dABCD resulting in smallest error is taken to be the final estimate • The more frequencies used, the better the estimate • RIPS uses 10 frequencies

  27. Localization • RIPS provides ranging estimates between sets of 4 nodes, not pairs of nodes directly • Would require solving a large number of nonlinear equations • Uses a Genetic Algorithm (GA) as a baseline instead

  28. Tuning Results • Good interference signals measured at double the communication range of the radios (160:80 meters) • Frequency and Phase TuningComparisons:

  29. Tuning Results • Mean error in phase measurements using varying amplitude filter thresholds

  30. Ranging Results • Algorithm for estimating interference signal frequency and phase offsets determines the average amplitude of the signal which correlates strongly with the error of the estimate

  31. Better Ranging Results

  32. Localization Results

  33. Limitations • Maximum localizable range between transmitters and receivers is defined by the radio range • Transmitters must be within 2 radio ranges of each other to create a successful interference signal

  34. Conclusions • Relies on two nodes transmitting a high-frequency carrier signal at slightly different frequencies • The resulting interference signal has a low beat frequency and can be measured at receiving nodes with cheap hardware • Relative phase offsets measured at two receivers is a function of the distances between the four nodes and the carrier frequency • With at least 8 nodes, it is possible to localize each node in 3D space • Achieves a localization accuracy of 3cm and a range of up to 120 meters

  35. Reference • Sha, L. et al. “Priority Inheritance Protocols: An Approach to Real-Time Synchronization.” IEEE Transactions on Computers, Vol. 39, No. 9, Sept 1990.

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