János Sallai

Sensor network-based countersniper system

An ad-hoc wireless sensor network-based system is presented that detects and accurately locates shooters even in urban environments. The system consists of a large number of cheap sensors communicating through an ad-hoc wireless network, thus it is capable of tolerating multiple sensor failures, provides good coverage and high accuracy, and is capable of overcoming multipath effects. The performance of the proposed system is superior to that of centralized countersniper systems in such challenging environment as dense urban terrain. In this paper, in addition to the overall system architecture, the acoustic signal detection, the most important middleware services and the unique sensor fusion algorithm are also presented. The system performance is analyzed using real measurement data obtained at a US Army MOUT (Military Operations in Urban Terrain) facility.

Countersniper system for urban warfare

An ad-hoc wireless sensor network-based system is presented that detects and accurately locates shooters even in urban environments. The localization accuracy of the system in open terrain is competitive with that of existing centralized countersniper systems. However, the presented sensor network-based solution surpasses the traditional approach because it can mitigate acoustic multipath effects prevalent in urban areas and it can also resolve multiple simultaneous shots. These unique characteristics of the system are made possible by employing novel sensor fusion techniques that utilize the spatial and temporal diversity of multiple detections. In this article, in addition to the overall system architecture, the middleware services and the unique sensor fusion algorithms are described. An analysis of the experimental data gathered during field trials at US military facilities is also presented.

Radio interferometric tracking of mobile wireless nodes

Location-awareness is an important requirement for many mobile wireless applications today. When GPS is not applicable because of the required precision and/or the resource constraints on the hardware platform, radio interferometric ranging may offer an alternative. In this paper, we present a technique that enables the precise tracking of multiple wireless nodes simultaneously. It relies on multiple infrastructure nodes deployed at known locations measuring the position of tracked mobile nodes using radio interferometry. In addition to location information, the approach also provides node velocity estimates by measuring the Doppler shift of the interference signal. The performance of the technique is evaluated using a prototype implementation on mote-class wireless sensor nodes. Finally, a possible application scenario of dirty bomb detection in a football stadium is briefly described.

Sensor node localization using mobile acoustic beacons

We present a mobile acoustic beacon based sensor node localization method. Our technique is passive in that the sensor nodes themselves do not need to generate an acoustic signal for ranging. This saves cost, power and provides stealthy operation. Furthermore, the beacon can generate much more acoustic energy than a severely resource constrained sensor node, thereby significantly increasing the range. The acoustic ranging method uses a linear frequency modulated signal that can be accurately detected by matched filtering. This provides longer range and higher accuracy than the current state-of-the-art. The localization algorithm was especially designed to work in such acoustically reverberant environment, as urban terrain. The algorithm presented handles non-Gaussian ranging errors caused by echoes. Node locations are computed centrally by solving a global non-linear optimization problem in an iterative and incremental fashion

Mobile sensor localization and navigation using RF doppler shifts

Many wireless sensor network applications require knowledge of node placement in order to make sense of sensor data in a spatial context. Networks of mobile sensors require position updates for navigation through the sensing region. The global positioning system is able to provide localization information, however in many situations it cannot be relied on, and alternative localization methods are required. We propose a technique for the localization and navigation of a mobile robot that uses the Doppler-shift in frequency observed by stationary sensor nodes. Our experimental results show that, by using observed RF Doppler shifts, a robot is able to navigate through a sensing region with an average localization error of 1.68 meters.

RF doppler shift-based mobile sensor tracking and navigation

Mobile wireless sensors require position updates for tracking and navigation. We present a localization technique that uses the Doppler shift in radio transmission frequency observed by stationary sensors. We consider two scenarios. In the first, the mobile node is carried by a person. In the second, the mobile node controls a robot. In both approaches the mobile node transmits an RF signal, and infrastructure nodes measure the Doppler-shifted frequency. Such measurements enable us to calculate the position and velocity of the mobile transmitter. Our experimental results demonstrate that this technique is viable and accurate for resource-constrained mobile sensor tracking and navigation.

InTrack: high precision tracking of mobile sensor nodes

Radio-interferometric ranging is a novel technique that allows for fine-grained node localization in networks of inexpensive COTS nodes. In this paper, we show that the approach can also be applied to precision tracking of mobile sensor nodes. We introduce in Track, a cooperative tracking system based on radio-interferometry that features high accuracy, long range and low-power operation. The system utilizes a set of nodes placed at known locations to track a mobile sensor. We analyze how target speed and measurement errors affect the accuracy of the computed locations. To demonstrate the feasibility of our approach, we describe our prototype implementation using Berkeley motes. We evaluate the system using data from both simulations and field tests.

High-accuracy differential tracking of low-cost GPS receivers

In many mobile wireless applications such as the automated driving of cars, formation flying of unmanned air vehicles, and source localization or target tracking with wireless sensor networks, it is more important to know the precise relative locations of nodes than their absolute coordinates. GPS, the most ubiquitous localization system available, generally provides only absolute coordinates. Furthermore, low-cost receivers can exhibit tens of meters of error or worse in challenging RF environments. This paper presents an approach that uses GPS to derive relative location information for multiple receivers. Nodes in a network share their raw satellite measurements and use this data to track the relative motions of neighboring nodes as opposed to computing their own absolute coordinates. The system has been implemented using a network of Android phones equipped with a custom Bluetooth headset and integrated GPS chip to provide raw measurement data. Our evaluation shows that centimeter-scale tracking accuracy at an update rate of 1 Hz is possible under various conditions with the presented technique. This is more than an order of magnitude more accurate than simply taking the difference of reported absolute node coordinates or other simplistic approaches due to the presence of uncorrelated measurement errors.

Radio interferometric angle of arrival estimation

Several localization algorithms exist for wireless sensor networks that use angle of arrival measurements to estimate node position. However, there are limited options for actually obtaining the angle of arrival using resource-constrained devices. In this paper, we describe a radio interferometric technique for determining bearings from an anchor node to any number of target nodes at unknown positions. The underlying idea is to group three of the four nodes that participate in a typical radio interferometric measurement together to form an antenna array. Two of the nodes transmit pure sinusoids at close frequencies that interfere to generate a low-frequency beat signal. The phase difference of the measured signal between the third array node and the target node constrains the position of the latter to a hyperbola. The bearing of the node can be estimated by the asymptote of the hyperbola. The bearing estimation is carried out by the node itself, hence the method is distributed, scalable and fast. Furthermore, this technique does not require modification of the mote hardware because it relies only on the radio. Experimental results demonstrate that our approach can estimate node bearings with an accuracy of approximately 3° in 0.5 sec.

Weapon classification and shooter localization using distributed multichannel acoustic sensors

A wireless sensor network-based wearable countersniper system prototype is presented. The sensor board is connected to a small helmet-mounted microphone array that uses time of arrival (ToA) estimates of the ballistic shockwave and the muzzle blast to compute the angle of arrival (AoA) of both acoustic events. A low-power radio is used to form an ad-hoc multihop network that shares the detections among the nodes. Utilizing all available ToA and AoA data, a novel sensor fusion algorithm then estimates the shooter position, bullet trajectory, miss distance, caliber, and weapon type. A single sensor relying only on its own detections is able determine the shooter position when both the shockwave and the muzzle blast are detected by at least three microphones each. Even with just one shockwave and one muzzle blast detection, the miss distance and range can be accurately estimated by a single sensor. The system has been tested multiple times at the US Army Aberdeen Test Center and the Nashville Police Academy. The demonstrated performance is 1-degree trajectory precision, over 95% caliber estimation accuracy, and close to 100% weapon estimation accuracy for 4 out of the 6 guns tested.