Name
Abstract | ||
|---|---|---|
Road networks are one of important surveillance areas in military scenarios. In these road networks, sensors will be sparsely deployed (hundreds of meters apart) for the cost-effective deployment. This makes the existing localization solutions based on the ranging ineffective. To address this issue, this paper introduces a novel approach based on the passive vehicular traffic measurement, called Autonomous Passive Localization (APL). Our work is inspired by the fact that vehicles move along routes with a known map. Using binary vehicle-detection time stamps, we can obtain distance estimates between any pair of sensors on roadways to construct a virtual graph composed of sensor identifications (i.e., vertices) and distance estimates (i.e., edges). The virtual graph is then matched with the topology of the road map, in order to identify where sensors are located on roadways. We evaluate our design outdoors on Minnesota roadways and show that our distance estimate method works well despite traffic noises. In addition, we show that our localization scheme is effective in a road network with 18 intersections, where we found no location matching error, even with a maximum sensor time synchronization error of 0.07 sec and a vehicle speed deviation of 10 km/h. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/TC.2010.260 | IEEE Trans. Computers |
Keywords | Field | DocType |
prefiltering,graph matching.,cost-effective sensor deployment,road vehicles,distance estimate,location matching error,binary vehicle-detection time stamp,minnesota roadway,autonomous passive localization algorithm,military vehicles,traffic noise,localization scheme,maximum sensor time synchronization,passive vehicular traffic measurement,sensor network,virtual graph,maximum sensor time synchronization error,passive localization,radionavigation,road network,mobile radio,military scenario,road sensor network,road map,distance estimation,road sensor networks,surveillance area,time stamp,graph theory,wireless sensor networks,road traffic,binary vehicle detection,road map topology,binary vehicle detection time stamp,distance estimate method,sensor placement,existing localization solution,vehicle speed deviation,known map,sensor identification,graph matching,servers,wireless sensor network,network topology,cost effectiveness,topology | Graph theory,Mobile radio,Computer science,Road map,Network topology,Real-time computing,Matching (graph theory),Ranging,Timestamp,Wireless sensor network | Journal |
Volume | Issue | ISSN |
60 | 11 | 0018-9340 |
Citations | PageRank | References |
7 | 0.47 | 28 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jaehoon Jeong | 1 | 387 | 34.96 |
| Shuo Guo | 2 | 525 | 21.95 |
| Tian He | 3 | 6869 | 447.17 |
| David H. C. Du | 4 | 1052 | 90.79 |