ALCYONESYSTEMS

Frank MoreseFounder/Chairman

SensNav™ 3D Locator SystemAlcyone Systems, LLC

http://www.alcyonesystems.com

Deploying a 3D Locator System based on a

Wireless Sensor Network Architecture

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Problem Statement• Lack of Situational Awareness

– Incident Commander & First Responder

• Lack of Real Time Monitoring– Search & Rescue Missions

• Navigational Blackouts– In Buildings, Structures, Cities & Canyons

• Poor Interoperability Between Agencies

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First Responder Network Needs

• System needs to scale to over 200+ nodes

• Capability to locate citizens in a search & rescue situation

• Solutions must require no infrastructure

• Radios must be robust in harsh environments

• Need for fast deployable reconfigurable networks

• Solution must integrate seamlessly in existing networks

• System needs to adapt to various application requirements

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Network Issues

• First responders often cluster

• Direct path to Incident Commander is likely not possible

– Must count on many hops and indirect paths to get there

• Must have sufficient connectivity for navigation & localization purposes

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Network Issues (cont.)

• Conditions will vary widely– Number of players

– Distribution of players

– Network connectivity

• Large networks are real possibility– Must protect against traffic overload

• Must guard against RF flooding– Too many transmissions in our fixed bandwidth could lead to a

serious degradation in RF performance

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Wireless Sensor Network Characteristics

• Number of nodes > 200+• Density of nodes (Clusters)• Pattern of node deployment• Radio Front End Architecture • Number of hops in the network• Traffic pattern• Limited Bandwidth

– Data generation rate, etc

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Multi-Sensor Data Fusion

• To overcome sensor failures, technological limitations, spatial, and temporal coverage problems, three properties must be ensured:

– Cooperation

– Redundancy

– Complementary

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SensNav™

Fusion Technology• SensNav™ Fusion

Schemes– Complementary

• Sources S1 and S2 provide different pieces of information, a and b, respectively, that are fused to achieve a broader information, denoted by (a+b)

– Redundant• Sources S2 & S3 provide the same

information, b, which is fused to obtain more accurate information, (b).

– Cooperative• Sources S4 and S5, provide

different information, c and c', that are fused into (c), which better describes the scene compared to c and c' individually.

(a + b)

ComplementaryFusion

B

(b) (c)

RedundantFusion

CooperativeFusion

S1 S2 S3 S4 S5

A C

a bb c'c

FusedInformation

InformationFusion

Sources

Information

Types of information fusion based on the relationship among the sources

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SensNav™

Distributed Algorithm• Does not require any calibration

• Does not require an infrastructure of accurate clocks (e.g., GPS)

• Each node’s clock is assumed to run reliably but asynchronously with respect to the other nodes– i.e., they can run at slightly different rates because of hardware (oscillator)

inaccuracies.

• Provides a mathematical way to compensate for these clock differences in order to arrive at a very precise timestamp recovery that in turn leads to a precise distance determination.

• Each node is able to determine the clock characteristics of other nodes in its neighborhood allowing network synchronization.

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SensNav™

High Performance WSN Platform• Multi-band/multi-radio

– Enables high interference tolerance

– Low latency

– High mesh-networking performance

• High tolerance against link errors can be achieved by transmitting redundant data in different routes and frequency channels.

• Drastically reduces hop delay due to data buffering and channel access delays.

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SensNav™

WSN Architecture• Our technology uses a hybrid approach combining

the attributes of a:

– High Performance wireless sensor network topology

– Wireless Ad-hoc reconfigurable cluster network

– Wireless local area network

• Architecture integrates these networks with

proprietary optimized algorithms and protocols

• SensNav™ utilizes a robust intra & inter cluster

communications network.

• SensNav™ has a novel (patent pending) approach

to the effective fusion of navigation and sensor data

without requiring the existence of a specific sensor

suite.

= Border Nodes (Intra- & Inter-links)

= Cluster Node (Intra-links only)

= Orphan node (Inter-link only)

PseudoliteInter-link

Inter-Cluster “Local-Area”

Link

Intra-Cluster “Personal Area”

Link

= Pseudolite (Inter-link only)

Networked Cluster

= Incident Command Post- Base Station

Long-Haul Links(High Power Links) to IC Base Station

Via Pseudolites

Direct Cluster to IC Base

Station “Local-Area” Link

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SensNav™

Personal 3D Locator System Architecture• SensNav™ uses multiple sensors, subsystems, &

algorithms to determine the location of the tracked personnel.

• Personal Locator architecture design comprises of:– Modular multi-sensor software stacks

– High performance embedded processor

– High performance fusion engine

– RF ranging module

– GPS receiver module

– Inertial navigation module

• Data from each subsystem is fused onboard the Personal Locator & Locator Command Station.

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SensNav™

RCLAD Sensor Technology• High resolution Thru-Wall Sensing

• Multiple beams for rapid scanning

• Detects via biometric signatures

– posture sway, respiration & heart beat

• Utility for First Responders

Remote Casualty Location Assessment Device (RCLAD)

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SensNav™

Incident Scene with Our Solution

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SensNav™

Observations• Cluster communication is localized

– Minimal interference to remote clusters

• Traffic is aggregated at single node within cluster– Minimizes network traffic to avoid congestion

• Sensor Data fusion can be done within the cluster – When navigation demands links outside the cluster, these can be

dynamically formed

• Since traffic is aggregated, most nodes rarely use the higher power network/ranging

• Ability to reroute when links are lost

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SensNav™

WSN Advantages• Our novel approach integrates the navigational sensors with a

Cluster based Wireless Sensor Network

• Topology is continuously changing, self-adapting to the connectivity and propagation conditions and to the traffic and user mobility patterns.

• The topology provides reliable and uninterruptible communication in harsh propagation conditions.

• Architecture is scalable to handle from small clusters to very large deployment of over 200 nodes with many clusters and vehicles.

• Lower power transmission for intra-cluster communications

– System guards against RF flooding