Acoustic Localisation

AVS | Acoustic Vector Sensor

Testkop6 AcousticVectorSensorAVS Microflown_SEMfotoPNG Click to enlarge

Acoustic Vector Sensors

Acoustic Vector Sensors (AVS) can detect, classify and locate all sorts of acoustic events in 3D space, for instance impulses, like Small Arms Fire (SAF), Rockets, Artillery, Mortars (RAM), but also tonal sound sources like ground vehicles and helicopters. AVS have a compact size (1cm), low weight (100 gram) and low power (<2 Watt), they can be deployed on all sorts of platforms, such as unattended ground sensors, vehicles, Unmanned Aerial Vehicles (UAV), dismounted soldiers and helicopters.

At any point in space, a sound field can be described completely by its two dimensions; the scalar value, and the vector value. The scalar value, sound pressure, is well known and well measured. But the other quantity in acoustics, the vector value Acoustic Particle Velocity, only recently became a directly measurable quantity with the invention of the Acoustic Vector Sensor (AVS) from Microflown.

The extremely small and light-weight Acoustic Vector Sensors are capable of detecting, localising, identifying and tracking sound sources in 3D space. This makes them beneficial for the defence industry, as source (target) locating sensors, increasing situational awareness. The key benefit of Acoustic Vector Sensors (AVS) is their ability to locate all types of sound sources from all types of platforms. Microflown's sensors are already established in the automotive industry, but the novel Acoustic Vector Sensors (AVS) are now being used for the detection and localisation of gunshots, artillery, aircraft and vehicles.

In acoustics this movement of air is called particle velocity. The Microflown sensor is based upon MEMS technology, and uses the temperature difference in the corss section of two extremely sensitivy platinum wires that are heated up to 200°C in order to determine Acoustic Particle Velocity. When air flows across the wires, the first wire cools down a little and due to heat transfer the air picks up some heat. Hence, the second wire is cooled down with the heated air and cools down less than the first wire. A temperature difference occurs in the wires, which alters their electrical resistance. This generates a voltage difference that is proportional to the Particle velocity and the effect is directional: when the direction of the airflow reverses, the temperature difference will reverse too.  

Assembling a sound pressure transducer and three orthogonally placed Microflown sensors in one single point, a very compact (5x5x5mm) AVS can be produced.  Direction and elevation of sound sources are direct outputs of the sensor. Further algorithms and/or additional Acoustic Vector Sensors allow distance to be determined.

The unique Acoustic Vector Sensor Technology means multiple sources can be located simultaneously even in complex situations such as urban environments or on noisy plaforms such as UAVs and ground vehicles.

    AVS Datasheet     


Improvements

Performance and operational improvements of Acoustic Vector Sensor compared to sheer pressure microphones based appreachers are numerous:

  • Low SWaP (Size, Weight and Power)
  • Better Angular accuracy
  • Better Range accuracy
  • Better CPA (Closest Point (of) Approach)
  • Broad-banded multi-treat localization capability 
  • Acoustic direction is a direct output

Acoustic sensing has traditionally been based upon using sound pressure transducers only. An array of several microphones is used to obtain a certain degree of directionality. The intermediate spacing in between the sound pressure transducers is the dominant factor, so the larger the array size, the lower the frequencies of the sound source can be localized. Hence dedicated arrays exist for either Small Arms Fire, or Mortars, or Helicopter localisation. Meaning it localizes merely one threat type per system!

In contrast to sheer pressure based microphones, Acoustic Vector Sensors (AVS) offer a multi-threat localization capability from 0.1 Hz to 20 kHz with one single AVS in 3D as depicted in the figure.

 

 

Currently these performance and operatianal improvements are translated in two different signatures that are differentiated i.e:

SAF | Small Arms Fire signature

RAM | Rocket Artillery Mortar signature

 


During the congress on Battlefield Acoustics held in April 2013 at the French German Institute Saint Louis (ISL), results indicated that when Small Arms where fired on a distance of 400 meter, pressure based microphone arrays show a reliability of 50%. (Meaning that in 50% of the cases the wrong Direction Of Arrival (DOA) is deduced.) Acoustic Vector Sensor based AMMS show way better results as can be infered from our latests scientific papers.

Besides the SAF and RAM signatures, Microflown AVISA is developing various signatures for e.g. Helicopters, Ground Vehicles and Sea Vessels. The current signatures are being implemented on numereous platforms.

Signal processing is required in order to convert the real time acoustic data to a relevant format and relate the relevant data to a timestamp and location. 

First, the signal is examined for relevant signatures (triggering). This can be in the time domain (e.g. gunshots), the time-frequency domain (e.g. Doppler of a passing propeller driven aircraft) or even in its time-frequency- DOA representation (e.g. tracking an aircraft using measurement data which is interrupted by gunfire). When such a signal is detected, it is determined if the signal is within preset limits (classification). If the signal is classified, models are applied to generate an appropriate output.

When linked, these outputs are combined to improve the classification precision and the localization accuracy.

The picture below shows an example from a time-frequency-level-DOA representation of the output of a single AVS of an airplane flyover at a military shooting range in the presence of gunshots and a nearby diesel engine. The time is shown on the x-axis, the frequency is on the y-axis, the level is represented with the brightness of the color and the color represents the DOA as indicated in the legend (right).

The gunshots are seen as the vertical lines in the graph. Such signals can be detected, classified and then can be filtered in or out. The diesel engine in this example generates two harmonics at 55Hz and 110Hz. Because the DOA is not changing, the color remains the same. The color shows that both the gunshots and the diesel engine are located to the south west. 

The airplane remains as a Doppler frequency shifted, and DOA varying, signal. This signal is relatively easy to detect and classify. One can already tell its heading by the color, traveling from the south east to the north east. Out of the change in DOA over the ground and the Doppler shift it is also possible to calculate the closest approach distance, the elevation, the speed and the true engine RPM of the aircraft.

When the above information is displayed on a map to the operator, the following layers could be toggled on and off depending on specific threats or sources of interest:

  • Impulsive noise sources
  • Fast mving sources
  • Slow moving sources
  • Static sources
  • Certain angular range on/off
  • Elevation low (ground) or in air (aircraft)