Acoustic Vector Sensors (AVS): Revolutionizing Battlefield Surveillance Against RAM, Ground Vehicles, and UAVs

Acoustic Vector Sensors: The Stealthy Game-Changer in Modern Military Surveillance

How next-gen AVS technology is reshaping battlefield intelligence—from drone detection to sniper localization and naval defense.

Acoustic sensor networks have become a vital component of modern military defense systems, offering an advanced capability to detect, classify, and neutralize threats based on sound signatures. These networks consist of an array of microphones and hydrophones that can detect airborne and underwater sound waves, providing real-time intelligence on enemy movements, missile launches, drone activity, and battlefield artillery fire. The ongoing Russia-Ukraine war has demonstrated the increasing reliance on unmanned aerial vehicles (UAVs) and loitering munitions, which necessitate more robust countermeasures. Acoustic sensors play a crucial role in anti-drone defense, artillery detection, and counter-sniper operations, making them indispensable in modern warfare.

This article explores the principles of acoustic sensor networks, their military applications, challenges, and future advancements in defense and security.

 The Role of Sensors in Modern Warfare

In modern warfare, information dominance is critical, and data collection relies heavily on sensors deployed across various platforms, including aircraft, unmanned aerial vehicles (UAVs), ground vehicles, and even soldier-worn systems. The vision for modern sensors is to enable complete situational awareness in all-weather conditions, day and night, beyond-line-of-sight, and through both natural and man-made obstructions.

Electronic sensors play a dominant role in modern battlefields, supporting a wide range of military applications. These include sensors and seekers for smart weapons, Positioning, Navigation, and Timing (PNT) sensors such as MEMS accelerometers and gyroscopes, Fiber Optic Gyroscopes (FOG), and Ring Laser Gyroscopes (RLG). Acoustic sensors such as fiber optic acoustic sensors, hydrophones, and surface acoustic wave (SAW) sensors, along with CBRNE sensors for detecting chemical, biological, radiological, nuclear, and explosive threats, are also crucial components of military sensor systems.

The ongoing Russia-Ukraine war has demonstrated the critical role of sensors, especially in countering UAV threats. Both sides have deployed drones extensively for reconnaissance, precision strikes, and electronic warfare, highlighting the growing need for effective UAV detection and neutralization. Acoustic sensor networks have emerged as a crucial component in detecting and tracking drones, particularly in environments where radar and optical systems face limitations due to terrain, weather conditions, or electronic countermeasures.

Principles of Acoustic Sensor Networks

Sound is created by a vibrating object and propagates as a wave through a medium such as air, water, or solid materials. As a result, sound cannot travel in the vacuum of space. Acoustic and seismic sensors leverage this principle to provide several advantages in battlefield applications.

Acoustic sensor networks function by detecting sound waves and processing them to identify their sources. These sensors work based on the direction of arrival (DoA), frequency analysis, and machine learning-based classification. The primary principle behind these networks is the triangulation of sound sources, where multiple sensors analyze incoming sound waves to determine the location and nature of the target. Sound wave signatures are unique for different military threats—missile launches produce a distinct acoustic pattern, while drones generate low-frequency humming noises that can be identified against background noise.

One of the key aspects of acoustic sensing is signal processing, which involves filtering out ambient noise, classifying sound sources, and tracking moving threats.

Signal Processing for Acoustic and Seismic Sensors

Signal processing plays a critical role in extracting valuable intelligence from acoustic and seismic sensor data. Key processes include target detection algorithms, feature extraction, target classification, and target tracking algorithms. Advanced signal processing techniques improve detection accuracy and reduce false alarms, enhancing the overall effectiveness of these sensor systems in combat environments. Machine learning algorithms are increasingly being used to differentiate between civilian and military sound sources, ensuring precision in target identification. Additionally, acoustic sensors can be deployed in both urban and rural environments, enabling militaries to monitor threats over vast areas.

Military Applications of Acoustic Sensor Networks

These sensors offer non-line-of-sight (NLOS) detection, fully passive operation (which enhances stealth and reduces power consumption), and panoramic (360°) coverage. Additionally, they enable non-cooperative target recognition (NCTR) since the acoustic and seismic signatures of some targets, such as helicopters, contain highly distinctive features. These systems are also cost-effective and potentially expendable, making them suitable for large-scale deployment.

Acoustic sensors play a crucial role in detecting and tracking ground and aerial vehicles, gunfire, mortars, and rockets by analyzing distinct sound signatures in the environment. These sensors provide real-time situational awareness, enabling security forces to pinpoint hostile activity with precision. Additionally, they are instrumental in identifying and classifying underwater threats, such as submarines, naval mines, and underwater improvised explosive devices (IEDs). Their capability to detect underground activity, including tunnel operations and underground fortified facilities (UGFs), makes them invaluable for counter-insurgency, border security, and anti-terrorism operations.

Acoustic sensor networks have a wide range of military applications, with a major focus on drone detection and counter-UAV operations. The Russia-Ukraine war has highlighted the strategic role of drones in reconnaissance, kamikaze attacks, and battlefield surveillance, prompting the need for better detection methods. Acoustic sensors can detect the characteristic sounds of UAV propellers, allowing defense systems to activate jamming or interception mechanisms before an attack occurs. This capability is particularly useful against stealth drones, which are difficult to track using radar but still produce identifiable acoustic signatures.

Another critical application is artillery and missile launch detection. Acoustic sensors positioned near the battlefield can pick up the blast waves of artillery fire and track their trajectory using time-delay analysis. This technology is commonly used for counter-battery fire, allowing forces to locate and neutralize enemy artillery positions quickly. In urban warfare scenarios, counter-sniper detection is another essential function of acoustic networks. By analyzing the shockwaves and muzzle blasts produced by gunfire, these sensors can pinpoint sniper positions and help neutralize threats in real-time.

Underwater acoustic sensors, or hydrophones, extend the utility of acoustic sensor networks to naval defense. These sensors detect submarine movements, underwater drones, and enemy vessel activities. In modern naval warfare, anti-submarine operations rely on acoustic sensors to track hostile submarines, even in heavily contested waters. Given the increasing use of autonomous underwater drones, the role of hydrophones in maritime defense and early warning systems is expanding significantly.

Advancements in Acoustic Sensors

Traditional acoustic sensors, such as microphones, measure sound pressure. However, acoustic vector sensors provide an advanced alternative by detecting both the pressure and the particle motion associated with a sound wave. Unlike hydrophones, which measure only pressure changes, vector sensors measure the direction of sound propagation using measurements taken at a single point in space.

The motion of particles in a sound wave is described by displacement, velocity, and acceleration—each a vector quantity with both magnitude and direction. Vector sensors measure one of these quantities along with pressure. Some vector sensors measure pressure gradients, which are proportional to acceleration. A typical vector sensor is constructed using two geophones to measure particle velocity and a standard hydrophone to measure pressure.

Advances in Vector Sensor Technology

While hydrophones remain the most common underwater acoustic sensors, vector sensors have been widely used in U.S. Navy Directional Frequency Analysis and Recording (DIFAR) sonobuoys for many years. The DIFAR sensor consists of an omnidirectional hydrophone and two particle motion sensors, positioned at right angles to each other, to measure horizontal components of sound wave motion. This design allows DIFAR sensors to determine the direction of incoming sound waves while rejecting noise from other directions, thus improving the signal-to-noise ratio (SNR).

Recent advances in single-crystal piezoelectric materials have enabled the development of much smaller vector sensors without sacrificing sensitivity. Modern three-dimensional (3D) vector sensors, using separate single-crystal accelerometers and hydrophones, can fit within compact housings as small as 0.8 inches in diameter and 3.125 inches in length. This miniaturization enhances deployment flexibility and reduces self-noise, enabling wider adoption of vector sensor technology in military applications.

Microflown Technologies and Acoustic Vector Sensors

Microflown Technologies Ltd., Netherlands, has pioneered Acoustic Vector Sensor (AVS) technology, offering a next-generation Intelligence, Surveillance, and Reconnaissance (ISR) solution that accurately differentiates and identifies attack sources by sensing high- and low-frequency sounds generated by weapons. Unlike traditional acoustic sensors, AVS technology measures acoustic particle velocity—the average velocity of moving air particles—rather than just sound pressure. This capability enables AVS to detect, classify, and track hostile threats such as gunshots, artillery, mortars, aircraft, ground vehicles, and helicopters with exceptional accuracy.

Unlike traditional microphone arrays, which require multiple distributed microphones to determine sound source locations, AVS achieves directional sound detection using a single compact sensor. This results in higher acoustic bandwidths, lower system size, reduced data transmission between nodes, and improved deployment flexibility. The micro-electromechanical system (MEMS)-based AVS unit (5x5x5 mm) integrates a sound pressure transducer and three orthogonally positioned Microflown sensors, enabling 3D detection and localization of hostile sources within one second, with an accuracy of approximately 1 degree. These compact sensors can be mounted on vehicles, UAVs, and dismounted soldiers, significantly enhancing battlefield awareness.

The AVS-equipped systems offer real-time target acquisition, threat detection, and situational awareness across diverse operational environments. By integrating Microflown’s MFSC-4, a 4-channel signal conditioner, the AVS system enhances signal amplification, phase correction, and real-time acoustic data conversion. These sensors are adaptable for deployment on unmanned aerial vehicles (UAVs) for aerial reconnaissance, armored vehicles for 360° battlefield surveillance, unattended ground sensor (UGS) networks for border security, and helicopters for detecting low-altitude aerial threats. According to research by de Bree and Druyvesleyn (Euronoise, 2009), a multi-node AVS network can track up to 4n² uncorrelated sources in a 3D battlespace, with recent studies suggesting up to 8n² sources can be detected when operating in broadband conditions.

At the core of Microflown’s AVS technology is its MEMS-based particle velocity sensor, which operates on the principle of thermal anemometry. Two ultra-sensitive platinum wires, heated to 200°C, measure temperature differences as air moves across them. When an acoustic wave passes, the first wire cools slightly, transferring heat to the moving air, which causes the second wire to cool down less than the first. This temperature differential alters the electrical resistance of the wires, generating a voltage difference proportional to the particle velocity and airflow direction. This fundamental principle enables ultra-precise acoustic direction-finding and tracking, even in highly dynamic battlefield conditions.

Ongoing research is integrating AI-driven acoustic signal processing to refine automatic classification of battlefield sound sources, distinguishing between enemy and friendly fire, and improving tracking of UAV swarms and stealth aircraft. Microflown’s next-generation AVS units are also being tested for submarine and underwater surveillance, using passive sonar arrays to track hostile naval assets and unmanned underwater vehicles (UUVs). The technology’s adaptability makes it a crucial asset for modern defense and security forces seeking to enhance multi-domain situational awareness across air, land, and sea operations.

Applications of Acoustic Vector Sensors (AVS) in Defense and Law Enforcement

Gunshot Detection and Law Enforcement Applications

Acoustic Vector Sensors (AVS) have proven to be an invaluable tool in law enforcement applications, particularly in gunshot detection systems like ShotSpotter. In a real-world example, Wilmington police successfully utilized ShotSpotter technology to pinpoint the exact location of gunfire, allowing officers to swiftly respond to the scene of a homicide. “This narrows the search down quite a bit and directs our officers pretty precisely and accurately as to where to go,” noted Wilmington Police Captain Jim Varrone. By deploying multiple acoustic sensors across urban environments, ShotSpotter detects gunshots in real-time, analyzes their unique acoustic signatures, and relays precise location data (latitude, longitude, and street address) to law enforcement agencies. This significantly enhances response times and officer safety while aiding forensic investigations by tracking gunfire patterns and incident histories.

Shooter Localization for Military Operations

The Defense Advanced Research Projects Agency (DARPA) has developed Shooter Localization technology under its Network Embedded Systems Technology (NEST) program to enhance battlefield awareness. Utilizing an ad-hoc wireless network of low-cost AVS nodes, the system detects the shockwave and muzzle blast produced by enemy gunfire. This data is transmitted in real-time to a base station, where AI-driven analysis pinpoints the shooter’s exact location with an accuracy of 1 meter and a latency of just 2 seconds. The rapid and precise localization of enemy combatants significantly reduces friendly casualties and improves counter-fire capabilities. Such systems are being integrated with soldier-worn and vehicle-mounted acoustic arrays, enabling real-time threat detection in urban and open battlefield environments.

Battlefield Surveillance and Target Classification

Wireless Sensor Networks (WSNs) based on acoustic vector sensing are instrumental in battlefield surveillance, border security, and moving target classification. Remotely deployed sensor nodes—positioned using UAVs, low-flying aircraft, or robotic ground vehicles—continuously monitor and relay acoustic, seismic, and visual data to command centers. These networks classify enemy assets by distinguishing between armored vehicles, light transport, and personnel movements based on their unique acoustic signatures. This capability is crucial for detecting covert enemy operations, tracking adversary convoys, and enhancing situational awareness for ground forces operating in contested environments.

Acoustic Detection of Low-Flying Helicopters and UAVs

Helicopters and low-flying UAVs can often evade radar and optical sensors by flying close to the ground and using natural terrain for cover. However, their rotor blades and engines produce distinct low-frequency acoustic signatures that travel long distances with minimal attenuation. Acoustic Vector Sensors are highly effective in detecting and classifying these airborne threats even when they are obscured by terrain, buildings, or foliage. Modern AVS-equipped defense systems leverage machine learning algorithms to differentiate between friendly and adversary helicopters while also estimating their distance, direction, and flight path—a critical advantage in countering low-altitude aerial threats.

Integration of AVS with UAV-Based Intelligence, Surveillance, and Reconnaissance (ISR)

Traditional UAV reconnaissance is primarily reliant on electro-optical and infrared sensors, which can be limited by weather conditions, visibility, and environmental obstructions. However, many battlefield events—such as gunfire, explosions, and vehicle movement—generate strong acoustic signatures that can be detected even when they are not visually apparent. Dutch company Microflown AVISA has pioneered AVS integration into UAV platforms, providing a multi-modal ISR capability. AVS-equipped UAVs can autonomously detect and locate enemy gunfire, explosions, and vehicle movements in real-time, offering a crucial advantage in modern asymmetric warfare.

Vehicle-Mounted AVS for 360° Battlefield Awareness

The Dutch Ministry of Defense has awarded Microflown AVISA a €1 million contract to integrate Acoustic Vector Sensors onto reconnaissance vehicles, armored personnel carriers, and tracked combat vehicles. This program aims to develop an all-around, full-spherical 3D acoustic situational awareness system that enhances crew survivability by detecting and localizing threats such as enemy sniper fire, artillery shelling, and approaching UAVs. The vehicle-mounted AVS system enables military forces to react preemptively to hostile engagements, significantly improving operational security in both urban and open battlefield environments.