Scaling a Distributed Sensor Array

Description:

Technology Description:

We present a method for adding a new sensor node to an existing distributed sensor array (DSA) through individual calibration of the new sensor node without having to recalibrate the entire system. Prior solutions for adding a new node to a DSA typically include performing a calibration procedure not only for the new node but for each existing node, which can introduce new errors, limiting accuracy, require vast processing power and time. UTD researchers have overcome these problems through an efficient closed form solution for individual calibration of a newly joined sensor by using signals emitted from spatially distributed sources to compute time difference of arrival (TDOA) measurements between existing DSA and the new sensor. These measurements, together with knowledge of array geometry and emitter positions, are then combined to estimate the new sensor position and synchronization offset with respect to other nodes in the DSA. The proposed method can handle the addition of multiple sensors either in parallel or sequentially. The spatially distributed sources may be arbitrary sources from the environment of the DSA. The method does not require source/sensor pairing as utilized in active methods. Furthermore, spatial source localization is built in to calibrate unknown sources.

Value Proposition:

An elegant solution for calibrating DSA information can provide for greater performance with respect to speed, accuracy, and cost reduction associated with contemporary DSA signal processing infrastructure.

Key Benefits:

Speed and Accuracy: Ability to add new sensor nodes to a DSA without extended calculation time and introduced errors associated with recalibrating the whole system.
Expandable: Efficient closed form solution for adding several individual sensor nodes (scaling) to a DSA system, and allows for the addition of multiple sensors either in parallel or sequentially.
Scalability: Easily expandable to other operating system-based devices (e.g., Tablets, iPads).
Flexible: Can use active or passive calibration techniques, as well as radio or acoustic waves emitter sources, which can be either known sources in the system or arbitrary sources in the environment.
Multi-Dimensional and Spatial Source Localization: Generally, performance of DSAs improve as more spatially-distributed sensors and/or emitters are added to the system.
Robust: Automatically recalibrates individual sensor nodes that move or get temporarily disconnected from the network.

Applications:

Wide Variety of Fields: radar, sonar, navigation, audio, and are useful for identifying and tracking the location of a target within a spatial area detectable by the DSA.
Target Identification.
Source Tracking.
Improving Signal Strength through Beam Forming.