Acoustic Vector Sensors
Acoustic Vector Sensors
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.
Microflown's technology means that passive broad banded acoustic radar systems are now a reality. The benefits as compared to sheer microphone based approaches are obvious, with their small size and weight, and as they can detect a variety of acoustic events from a variety of mounting platforms, a rapid expansion in AVS use for defence and security applications is expected.
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 Microflown sensor.
The Microflown sensor is based upon MEMS technology, and uses the temperature difference in the cross section of two extremely sensitive heated wires to determine the acoustic particle velocity. Instead, it measures the velocity of air across two tiny, resistive strips of platinum that are heated to 200°C. In fluid dynamics, the motion of gas or liquid is called a flow, hence the name Microflown, which is sensitive to the movement of air rather than fluctuating pressure.
In acoustics this movement of air is called particle velocity. When air flows across the strips, 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. In the case of a sound wave, the airflow across the strips alternates according to the waveform and this results in a corresponding alternating voltage.
Assembling a sound pressure transducer and three orthogonally placed Microflown sensors in one single point, a very compact (5x5x5mm) AVS can be produced. The amplitude differences across the Microflown sensors provide the direction and elevation of sound sources. Further algorithms and/or additional vector sensors allow distance to be calculated.
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)
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