400  Underwater Acoustic Sensor Networks (UWASNs)

Have you ever tried to use a walkie-talkie underwater? It doesn’t work! Radio waves can’t travel through water - they get absorbed almost immediately. So how do submarines communicate? The same way dolphins and whales do - with sound!

Underwater Sound Facts: - Sound travels about 1,500 meters per second in water (that’s faster than in air, but 200,000 times slower than radio!) - A message traveling 1 kilometer underwater takes almost 1 second to arrive - By the time your message arrives, a fast-moving fish might be 10 meters away from where you detected it!

Term Simple Explanation
UWASN Underwater Acoustic Sensor Network - uses sound instead of radio
Acoustic Communication Talking underwater using sound waves (like whales!)
AUV Autonomous Underwater Vehicle - a robot submarine
Propagation Delay The time it takes for a sound to travel from sender to receiver
Multipath Sound bouncing off the surface and seafloor, causing echoes
Trilateration Finding location using distances from multiple known points

Why this matters: Underwater sensor networks monitor oil pipelines, track submarines, study marine life, and detect tsunamis. The slow speed of sound makes tracking underwater targets much harder than on land!

400.1 Learning Objectives

By the end of this chapter, you will be able to:

  • Understand Acoustic Communication: Explain why radio doesn’t work underwater and how acoustic communication differs
  • Analyze Propagation Delays: Calculate latency impact on tracking accuracy for underwater targets
  • Model Oceanic Forces: Describe how currents, waves, and tides affect underwater node mobility
  • Apply HASL Protocol: Explain High-Speed AUV-Based Silent Localization for energy-efficient positioning
  • Design Opportunistic Localization: Plan iterative localization strategies with minimal infrastructure
  • Compensate for Latency: Apply motion prediction techniques for stale position estimates

400.2 Prerequisites

Before diving into this chapter, you should be familiar with:

400.3 UWASN Characteristics

Time: ~10 min | Difficulty: Advanced | Unit: P05.C41.U03

Underwater environments present unique challenges: no radio propagation, high latency, node mobility from ocean currents.

400.3.1 UWASN Architecture

%% fig-alt: "Diagram showing IoT architecture components and their relationships with data flow and processing hierarchy."
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graph TB
    subgraph Surface["Ocean Surface"]
        Buoy1[Surface Buoy<br/>Anchor]
        Buoy2[Surface Buoy<br/>Anchor]
        Gateway[Gateway<br/>Satellite Uplink]
    end

    subgraph Underwater["Underwater Network - Acoustic Communication"]
        Sub1[Sensor Node 1]
        Sub2[Sensor Node 2]
        Sub3[Sensor Node 3]
        AUV[AUV Mobile<br/>Collector]
    end

    Sub1 & Sub2 & Sub3 -.->|Acoustic<br/>1500 m/s| AUV
    AUV -.->|Acoustic| Buoy1
    Buoy1 -->|Radio| Gateway
    Buoy2 -.->|Acoustic<br/>Localization| Sub2

    style Sub1 fill:#16A085,stroke:#2C3E50,color:#fff
    style Sub2 fill:#16A085,stroke:#2C3E50,color:#fff
    style Sub3 fill:#16A085,stroke:#2C3E50,color:#fff
    style AUV fill:#E67E22,stroke:#2C3E50,color:#fff
    style Buoy1 fill:#2C3E50,stroke:#16A085,color:#fff
    style Buoy2 fill:#2C3E50,stroke:#16A085,color:#fff
    style Gateway fill:#2C3E50,stroke:#16A085,color:#fff

Figure 400.1: Underwater Acoustic Sensor Network (UWASN) architecture

Underwater Acoustic Sensor Network (UWASN) architecture showing acoustic communication (1500 m/s propagation creating high latency), surface buoy anchors for localization, mobile AUV for data collection, and gateway with satellite uplink. Challenges include multipath interference, Doppler shifts from currents, and limited bandwidth (1-10 kbps).

400.3.2 Key Challenges

Table 400.1: UWASN Challenges
Challenge Description Impact
Acoustic propagation Sound waves instead of radio Low data rate (1-10 kbps)
High latency Speed of sound: 1500 m/s 0.67 ms per meter delay
Multipath Reflections from surface/bottom Signal distortion
Doppler effect Node mobility causes frequency shifts Difficult synchronization
Limited bandwidth Acoustic channel: 1-100 kHz Severe throughput limits
Energy constraints Battery replacement very expensive Must last years
Node mobility Ocean currents move nodes Dynamic topology

400.3.3 Latency Impact on Tracking

Propagation speed comparison: - RF in air: 3 x 10^8 m/s (speed of light) - Acoustic in water: 1,500 m/s (200,000x slower!)

Latency calculations: - 1 km underwater: 1000m / 1500 m/s = 0.67 seconds delay - 5 km underwater: 3.37 seconds delay - Compare: 5 km RF in air = 0.000017 seconds (negligible)

Tracking challenge example: - Submarine moving at 10 m/s travels 33.7 meters during 3.37s delay - Position estimate is 33.7 meters stale by the time it reaches base station!

400.4 Oceanic Forces Mobility Model

Underwater nodes don’t move randomly - they’re affected by physical oceanographic forces:

%% fig-alt: "Diagram showing IoT architecture components and their relationships with data flow and processing hierarchy."
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graph TB
    subgraph Forces["Oceanographic Forces Acting on Underwater Nodes"]
        Current[Ocean Currents<br/>0.1-2 m/s horizontal]
        Wave[Wave Motion<br/>Sinusoidal vertical]
        Tide[Tidal Flows<br/>12-hour cycles]
        Thermal[Thermal Stratification<br/>Density layers]
    end

    subgraph Node["Underwater Sensor Node"]
        Buoy[Buoyancy Device]
        Sensor[Sensor Package]
        Anchor[Anchor Cable]
    end

    subgraph Effects["Movement Effects"]
        Horizontal[Horizontal Drift<br/>10-100m per day]
        Vertical[Vertical Oscillation<br/>plus/minus 1-5m per wave]
        Dynamic[Dynamic Topology<br/>Requires re-localization]
    end

    Current -->|Push| Node
    Wave -->|Lift| Node
    Tide -->|Pull| Node
    Thermal -->|Buoyancy| Node

    Node -->|Results in| Effects

    style Current fill:#16A085,stroke:#2C3E50,color:#fff
    style Wave fill:#16A085,stroke:#2C3E50,color:#fff
    style Tide fill:#16A085,stroke:#2C3E50,color:#fff
    style Thermal fill:#16A085,stroke:#2C3E50,color:#fff
    style Sensor fill:#E67E22,stroke:#2C3E50,color:#fff
    style Horizontal fill:#2C3E50,stroke:#16A085,color:#fff
    style Vertical fill:#2C3E50,stroke:#16A085,color:#fff
    style Dynamic fill:#2C3E50,stroke:#16A085,color:#fff

Figure 400.2: Oceanographic forces affecting underwater sensor node mobility

Oceanographic forces affecting underwater sensor node mobility: ocean currents (0.1-2 m/s horizontal drift), wave motion (sinusoidal vertical oscillation plus/minus 1-5m), tidal flows (12-hour cycles), and thermal stratification (density-driven buoyancy changes). Nodes can drift 10-100m per day, requiring frequent re-localization and creating dynamic network topology challenges.

Key mobility factors:

Force Effect Magnitude
Ocean Currents Horizontal drift 0.1-2 m/s
Wave Motion Vertical oscillation plus/minus 1-5m per wave
Tidal Flows Periodic displacement 12-hour cycles
Thermal Stratification Buoyancy changes Density-driven vertical movement

Result: Nodes can drift 10-100m per day, requiring frequent re-localization

400.5 3D Localization in UWASNs

GPS doesn’t work underwater. Localization requires acoustic ranging from surface anchors.

400.5.1 HASL Protocol

HASL (High-Speed AUV-Based Silent Localization):

Diagram illustrating HASL (High-Speed AUV-Based Silent Localization) protocol where autonomous underwater vehicle (AUV) moves to multiple GPS-known positions broadcasting acoustic beacons, allowing underwater sensor nodes to passively calculate their 3D positions through trilateration without energy-costly transmission
Figure 400.3: HASL (High-Speed AUV-Based Silent Localization) using autonomous underwater vehicles for underwater sensor network localization 

%% fig-alt: "Diagram showing IoT architecture components and their relationships with data flow and processing hierarchy."
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sequenceDiagram
    participant AUV as AUV Mobile Anchor
    participant S1 as Sensor Node 1
    participant S2 as Sensor Node 2
    participant S3 as Sensor Node 3

    AUV->>AUV: Move to Position A<br/>(GPS-known)
    AUV->>S1: Broadcast Beacon<br/>(Position A, Time)
    AUV->>S2: Broadcast Beacon
    AUV->>S3: Broadcast Beacon

    Note over S1,S3: Nodes listen passively<br/>(Silent - No TX)

    S1->>S1: Measure ToA<br/>Calculate distance
    S2->>S2: Measure ToA<br/>Calculate distance
    S3->>S3: Measure ToA<br/>Calculate distance

    AUV->>AUV: Move to Position B
    AUV->>S1: Broadcast Beacon<br/>(Position B, Time)
    AUV->>S2: Broadcast Beacon
    AUV->>S3: Broadcast Beacon

    S1->>S1: Trilateration<br/>from A, B, C
    S2->>S2: Trilateration<br/>from A, B, C
    S3->>S3: Trilateration<br/>from A, B, C

    Note over S1,S3: Nodes localized<br/>without transmitting

Figure 400.4: HASL (High-Speed AUV-Based Silent Localization) protocol sequence

HASL (High-Speed AUV-Based Silent Localization) protocol: AUV moves to multiple GPS-known positions broadcasting beacons, underwater sensor nodes passively listen and measure time-of-arrival to calculate distances, then perform trilateration. Silent operation (no sensor transmission) saves massive energy compared to traditional localization requiring sensor responses.

HASL Benefits: - Silent: Nodes listen passively (no transmission = energy savings) - Mobile anchor: AUV provides multiple reference positions - Scalable: Single AUV localizes many nodes in one pass

Energy savings calculation: - Traditional: 100 sensors x 100 beacon responses/hour = 10,000 transmissions/hour - HASL: 5 AUV broadcasts/hour = 5 transmissions/hour - 99.95% reduction in acoustic channel usage

400.5.2 Opportunistic Localization

Illustration of opportunistic localization strategy in underwater acoustic sensor networks where initially localized nodes (anchored to surface buoys with GPS) iteratively assist unlocalized neighbor nodes to determine their positions through multi-hop acoustic ranging, achieving full network localization with minimal infrastructure
Figure 400.5: Opportunistic localization strategy leveraging mobile nodes and iterative position updates in underwater networks

Strategy: Localized nodes assist in localizing nearby unlocalized nodes.

Iterative Localization: - Round 1: 3 surface anchors -> localize 5 nearby nodes - Round 2: 5 localized nodes -> localize 12 more - Round 3: 17 localized -> localize remaining - Result: Full network localization with only 3 surface anchors

How it works: 1. Initially localized nodes (anchored to surface buoys with GPS) broadcast their positions 2. Unlocalized nodes measure distances to multiple localized neighbors 3. Using trilateration, unlocalized nodes calculate their positions 4. Newly localized nodes can now assist others 5. Process iterates until all nodes are localized

400.6 Motion Prediction for Stale Estimates

Solution approaches for latency compensation:

  1. Kalman Filter Prediction: Use motion model to predict current position from stale measurements
  2. Extended Kalman Filter (EKF): Handles non-linear motion patterns underwater
  3. HASL Integration: Combine AUV-based localization with motion prediction

Example: Submarine Tracking

Measured position: (100m, 200m, 50m) at time T
Propagation delay: 3.37 seconds
Estimated velocity: (10 m/s, 0 m/s, 0 m/s)

Predicted current position:
  x = 100 + (10 * 3.37) = 133.7m
  y = 200 + (0 * 3.37) = 200m
  z = 50 + (0 * 3.37) = 50m

Predicted position: (133.7m, 200m, 50m)

400.7 Knowledge Check

Question: In an underwater acoustic sensor network, signals propagate at ~1500 m/s. Over a 3 km link, the one-way propagation delay is approximately:

Explanation: Delay = distance / speed = 3000 m / 1500 m/s = 2 seconds. In tracking systems, multi-second propagation delays mean position updates can be stale, so prediction and delay-tolerant protocols become important.

Question: Underwater acoustic sensor networks (UASNs) use sound waves instead of radio for communication. What is the primary challenge this introduces for tracking underwater targets?

Explanation: Acoustic propagation speed: Sound in water travels ~1500 m/s (vs. electromagnetic waves in air: 3x10^8 m/s = 200,000x faster!). Tracking challenges: (1) High latency: Sensor 1 km from target -> acoustic signal takes 1000m / 1500m/s = 1 second to arrive. By the time sensor receives signal, target has moved! Fast submarine at 20 m/s travels 20m during 1-second delay. (2) Positioning errors: Trilateration using time-of-arrival (ToA) measures signal propagation time to estimate distance. With 1-second delays, even small timing errors create large positioning errors. (3) Multi-hop delays: 5-hop acoustic path to base station: 5 seconds delay. Position estimate is 5 seconds stale. (4) Dynamic topology: Ocean currents move sensors (attached to anchored buoys that drift). Network topology constantly changing, requiring frequent re-localization.

Comparison to terrestrial WSN: Radio at 100m: propagation delay 0.3 microseconds (negligible). Acoustic at 100m: 67 milliseconds (significant).

Data rates: Acoustic communication: 1-10 kbps (vs. terrestrial radio: 250 kbps Zigbee, 54 Mbps Wi-Fi). Limits video transmission, requires compression.

Solutions: (1) Motion prediction: Use Kalman filters to predict current position from stale measurements. (2) AUVs for localization: Autonomous Underwater Vehicles with known positions provide reference points for silent localization. (3) Opportunistic iterative localization: Nodes with uncertain positions gradually improve estimates through encounters with localized nodes.

Applications: Submarine tracking, underwater pipeline monitoring, marine life tagging, offshore structure inspection.

In underwater networks, HASL (High-Speed AUV-Based Silent Localization) uses mobile AUVs instead of fixed beacons. What makes the sensor nodes “silent” in this approach?

Options: - A) Sensors use optical signals instead of acoustic - B) Sensors only listen for AUV broadcasts; they do not transmit, saving massive energy - C) Sensors are physically quiet to avoid disturbing marine life - D) Sensors operate on low-frequency bands below audible range

Correct: B) Sensors only listen for AUV broadcasts; they do not transmit, saving massive energy

Traditional beacon localization (energy-expensive): 1. Fixed beacons broadcast positions periodically 2. Unknown nodes respond with measurements 3. Both sides transmit -> high energy consumption 4. Acoustic transmission is primary energy drain underwater

HASL silent localization: 1. AUV moves to GPS-known position (surfaces for GPS fix) 2. AUV broadcasts: “I am at position (x, y, z)” 3. Sensors LISTEN passively, measure time-of-arrival 4. Sensors calculate distance = sound_speed x time 5. Multiple AUV passes from different angles -> trilateration

Energy savings: - Traditional: 100 sensors x 100 beacon responses/hour = 10,000 transmissions/hour - HASL: 5 AUV broadcasts/hour = 5 transmissions/hour - 99.95% reduction in acoustic channel usage

Opportunistic extension: - Localized nodes assist unlocalized neighbors - Round 1: 3 surface anchors -> localize 5 nearby nodes - Round 2: 5 localized nodes -> localize 12 more - Round 3: Full network localization with minimal infrastructure

400.9 Summary

This chapter explored Underwater Acoustic Sensor Networks (UWASNs) and their unique challenges:

Acoustic Communication Fundamentals: - Sound travels at 1500 m/s underwater (200,000x slower than RF in air) - 1 km underwater link creates 0.67 second delay - Bandwidth limited to 1-10 kbps due to acoustic channel constraints

Major UWASN Challenges: - High Latency: Position estimates become stale during multi-second propagation delays - Multipath: Reflections from surface and seafloor distort signals - Node Mobility: Ocean currents drift nodes 10-100m per day - Energy Constraints: Battery replacement extremely expensive underwater

Localization Solutions: - HASL Protocol: AUV-based silent localization achieves 99.95% energy savings - Opportunistic Localization: Iterative positioning with minimal surface infrastructure - Motion Prediction: Kalman filtering compensates for stale position estimates

Oceanic Forces: - Currents: 0.1-2 m/s horizontal drift - Waves: Sinusoidal vertical oscillation - Tides: 12-hour periodic displacement - Thermal stratification: Density-driven buoyancy changes

Key Insights: - GPS doesn’t work underwater - must use acoustic ranging - Silent localization (receive-only sensors) dramatically reduces energy consumption - Motion prediction is essential for accurate tracking with multi-second delays

400.10 What’s Next

Continue to Nanonetworks to explore sensing and communication at molecular scales, enabling biomedical applications like targeted drug delivery and in-body health monitoring.