The robust estimation of multiple motions: parametric and piecewise-smooth flow fields
Computer Vision and Image Understanding
Dynamic fine-grained localization in Ad-Hoc networks of sensors
Proceedings of the 7th annual international conference on Mobile computing and networking
Fast bilateral filtering for the display of high-dynamic-range images
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Robust Positioning Algorithms for Distributed Ad-Hoc Wireless Sensor Networks
ATEC '02 Proceedings of the General Track of the annual conference on USENIX Annual Technical Conference
Range-free localization schemes for large scale sensor networks
Proceedings of the 9th annual international conference on Mobile computing and networking
The n-hop multilateration primitive for node localization problems
Mobile Networks and Applications
Localization from Connectivity in Sensor Networks
IEEE Transactions on Parallel and Distributed Systems
Robust distributed network localization with noisy range measurements
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Robust distributed node localization with error management
Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing
The effects of ranging noise on multihop localization: an empirical study
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Localization in sparse networks using sweeps
Proceedings of the 12th annual international conference on Mobile computing and networking
Challenges: device-free passive localization for wireless environments
Proceedings of the 13th annual ACM international conference on Mobile computing and networking
Flowcode: multi-site data exchange over wireless ad-hoc networks using network coding
MILCOM'09 Proceedings of the 28th IEEE conference on Military communications
IEEE Transactions on Image Processing
Beyond triangle inequality: sifting noisy and outlier distance measurements for localization
INFOCOM'10 Proceedings of the 29th conference on Information communications
Validating sensors in the field via spectral clustering based on their measurement data
MILCOM'09 Proceedings of the 28th IEEE conference on Military communications
Flowcode: multi-site data exchange over wireless ad-hoc networks using network coding
MILCOM'09 Proceedings of the 28th IEEE conference on Military communications
Empirical evaluation of signal-strength fingerprint positioning in wireless LANs
Proceedings of the 13th ACM international conference on Modeling, analysis, and simulation of wireless and mobile systems
Locating sensors in the wild: pursuit of ranging quality
Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems
A spectral clustering approach to validating sensors via their peers in distributed sensor networks
International Journal of Sensor Networks
The impact of sensor errors and building structures on particle filter-based inertial positioning
Pervasive and Mobile Computing
Robust localization against outliers in wireless sensor networks
ACM Transactions on Sensor Networks (TOSN)
Beyond triangle inequality: Sifting noisy and outlier distance measurements for localization
ACM Transactions on Sensor Networks (TOSN)
Refining hop-count for localisation in wireless sensor networks
International Journal of Sensor Networks
Localization of wireless sensor networks in the wild: pursuit of ranging quality
IEEE/ACM Transactions on Networking (TON)
RSSI-based relative localisation for mobile robots
Ad Hoc Networks
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We consider the problem of localizing wireless nodes in an outdoor, open-space environment, using ad-hoc radio ranging measurements, e.g., 802.11. We cast these ranging measurements as a set of distance constraints, thus forming an over-determined system of equations suitable for non-linear least squares optimization. However, ranging measurements are often subject to errors, induced by multipath signals and variations in path loss, unreliable hardware or antenna connectors, or imperfection in measurement models. Such potentially large, non-Gaussian errors in the measurement data ultimately produce inaccurate localization solutions. We propose a new error-tolerant localization method, called snap-inducing shaped residuals (SISR), to identify automatically "bad nodes" and "bad links" arising from these errors, so that they receive less weight in the localization process. In particular, SISR snaps "good nodes" to their accurate locations and gives less emphasis to other nodes. While the mathematical techniques used by SISR are similar to robust statistics, SISR's exploitation of the snap-in effect in localization appears to be novel. We provide analysis on the principle of SISR, illustrate errors in real-world measurements, and demonstrate a working SISR implementation in field experiments on a testbed of 37 wireless nodes, as well as show the superior performance of SISR in simulation with a larger number of nodes.