Extreme Low Frequency Hydrophone

Large aircraft can generate air vortices in their wake, turbulence that can prove hazardous to aircraft that follow too closely. Because wake vortices are invisible, all takeoffs at busy airports are spaced several minutes apart. This separation gives the vortices time to dissipate, even though they only occur 10% of the time, with resulting loss of operational efficiency. Similarly, clear air turbulence is invisible and can also be hazardous to aircraft. By detecting such disturbances through their infrasound emissions, precautions can be taken to avoid them. Other phenomena can be detected through infrasound, including tornadoes, helicopters on the other side of mountains, underground nuclear explosions and digging tunnels. Through the unique properties of infrasound, many of these can be detected from hundreds of miles away. NASA's infrasound sensor is a highly refined microphone that is capable of detecting acoustic waves from 20 Hz down to dc, the infrasound range. The design is robust and compact, eliminating the bulk and weight found in other technologies. Where most alternative methods are restricted to certain weather conditions and locations, the NASA sensor filters noise from wind and other sources, allowing its use under any weather or geographic conditions.

Acoustical studies of atmospheric events like convective storms, shear-induced turbulence, acoustic gravity waves, microbursts, hurricanes, and clear air turbulence over the last forty-five years have established that these events are strong emitters of infrasound (sound at frequencies below 20 Hz). Over the years, NASA Langley has designed and developed a portable infrasonic detection system which can be used to make useful infrasound measurements at a location where it was not possible previously. The system comprises an electret condenser microphone, and a small, compact windscreen. The system has been modified to be used in the air, underground, as well as underwater (to determine man-made and precursor to tsunami). The system also features a data acquisition system that permits real-time detection, bearing, and signature of a low frequency source. However, to determine bearing of the received signals, the microphones are to be arranged as an equilateral triangle with a certain microphone spacing. The spacing depends upon location of the microphone array. For a ground-based array, the microphone spacing of 100 feet (30.48m) is desired to determine time delay for signals arriving at each microphone location. The microphone spacing depends upon speed of sound through the array medium. For underwater array, the spacing between microphones would be around 1500 feet. The data acquisition system provides data output in the infrasonic bandwidth which is then analyzed using an adaptive algorithm (least-mean-squares time-delay-estimation) using modern computational power to locate source by plotting source location hyperbolas on-line. A smaller array size reduces the time resolution resulting in strong signal coherence. The innovation approach is to exploit modern signal processing methods, i.e. adaptive filtering, where computer is trained on-line to recognize features of the event to be detected. Modern computational capability permits the adaptive algorithm (least-mean-squares time-delay estimation or LMSTDE) which is vastly more powerful algorithm. This system has better resolution able to determine direction with arrived signals within five-degree accuracy.

Radiosondes are launched twice a day from different locations of the world and meteorological data is collected to plot the STUV diagram and determining CAPE (Cumulative Average Potential Energy) values. Radiosondes are not re-usable and used only at pre-determined locations around the globe. Moreover, a radiosonde can drift up to 125 miles from its release point. About 75,000 radiosondes are used every year. Given this unmet need, an inventor at NASA has developed an advanced airborne meteorological system which can provide meteorological parameters at any location at any desired time. In additional to routinely used meteorological sensors, an infrasonic sensor is also included to determine wind shear at local and regional levels. The airborne system may also be used in towns and cities to track drones and UAVs in the area. The airborne vehicle (UAV or drone) should be able to track seismic waves, magnetic storms, magneto-hydrodynamic waves, tornadoes, meteor, and lightning, etc. This technology can be use to measure environmental turbulence including wind shear, vortices as well as large and small eddies is an important factor in forecasting local and regional weather. It can also detect infrasound at ranges of many miles from the source and the shape of the acoustic power spectrum can be used to identify type of turbulence in the atmosphere.

Among the tests, landing gear cavities, a known cause of airframe noise, were evaluated. These are the regions where the landing gear deploys from the main body of an aircraft, typically leaving a large cavity where airflow can get pulled in, creating noise. NASA applied two concepts to these sections, including a series of chevrons placed near the front of the cavity with a sound-absorbing foam at the trailing wall, as well as a net that stretched across the opening of the main landing gear cavity. This altered the airflow and reduced the noise resulting from the interactions between the air, the cavity walls, and its edges.

A method for predicting the audibility of an arbitrary time-varying noise (signal) in the presence of masking noise is described in "An Algorithm for Statistical Audibility Prediction (SAP) of an Arbitrary Signal in the Presence of Noise" published in the Journal of the Audio Engineering Society (Vo. 69, No. 9, September 2021). The SAP method relies on the specific loudness, or loudness perceived through the individual auditory filters, for accurate statistical estimation of audibility vs. time. As such, this work investigated a new hypothesis that audibility is more accurately discerned within individual auditory filters by a higher-level, decision-making process. Audibility prediction vs. time is intuitive since it captures changes in audibility with time as it occurs, critical for the study of human response to noise. Concurrently, time-frequency prediction of audibility may provide valuable information about the root cause(s) for audibility useful for the design and operation of sources of noise. Empirical data, gathered under a three-alternative forced-choice (3AFC) test paradigm for low-frequency sound, has been used to examine the accuracy of SAPs. Future work should involve additional studies to examine the performance of SAP with realistic ambient noise and signals with higher-frequency content.