Aerospace and Electronic Systems Magazine November 2016 Tutorial X - 98


Sense and Avoid for Unmanned Aircraft Systems
sound, i.e., the speed of the signal that must be detected, is far
from constant during the travel because it depends on the thermodynamic properties of the material that transmits the wave. For
instance, the speed of sound is higher if the air is warmer and it is
lower if the air is colder and it changes with the frequency. As a
consequence, several unwanted effects can arise, such as echoes,
distortions, and nonlinearities. The type of acoustic signals that
are received by the microphone can be emitted by several sources
and in several cases they are not threats. The recognition of a
threat is performed also by estimating the spectral signature of
the sound received in order to perform a correlation analysis with
the spectral signature of an aircraft engine. Since some effects on
the transmitted sound can produce a spectral distortion, a negative impact on the recognition of a threat can arise, thus increasing the number of false alarms or missed detections.
A basic expression that permits to estimate the acoustic intensity received at a distance R from a sound source is given by (32):
	(32)
where I [W/m2] is the acoustic intensity, Q is the directivity index
of the source that has the same meaning of the gain G in the radar
equation (Q=1 for a source that has a spherical pattern and Q=2 for
hemispherical source), and W [W] is the sound power. In terms of
decibels, (32) can be reformulated as reported in (33):
	(33)
where Lp is the sound pressure level referred to the "threshold of
audibility" (dB re 2x10-5 N/m2 @ 1000 Hz), LW is the sound power
level (dB re 10-12 W @ 1000 Hz), DI is the directivity index DI =
10log10 (Q). DI is equal to 0 for an omni-directional source (Q=1).
The "threshold of audibility" is given by the condition expressed
in (34):
	(34)
This equation assumes that the capability to detect sounds of a microphone is similar to the one of the human ears.
Moreover, environmental effects can be added to (33), thus resulting in the form expressed by (35):
	(35)
where Aabs is the atmospheric absorption expressed in dB and AE
is the excess attenuation, i.e., the total attenuation in addition to
that due to spherical divergence and atmospheric absorption. Aabs
is a linear function of R, i.e. Aabs = αR where α can be calculated as
a function of frequency f [Hz], temperature T [K] and molar concentration of water vapor h (%) [25]. AE for airborne applications
is mainly determined by wind and turbulence. The determination
of this term is complex and requires the development of heavy experimental and numerical activities to be determined. A general
rule of thumb gives a 0 dB excess attenuation for calm weather,
whereas up to 15 dB can be determined by wind and turbulence.
98	

Consequently, the above reported expression (34) can be rewritten
in the form of (36):
	(36)
The determination of the initial detection range Rdet by means of
(34) is a complicated task to be carried out because it is a strongly
nonlinear function of R. Consequently, a first guess about Rdet can
be derived by exploiting (33) and applying further refinement and
analysis to estimate all terms in (36). The resulting value of Rdet is
given by (37):
		

(37)

For instance, a small piston engine aircraft can be assumed as a
spherical source (DI=0) with Lw=70 dB @ 1000 Hz, whereas a
large jet aircraft can be assumed as a spherical source (DI=0) with
Lw=90 dB @ 1000 Hz [26]. By applying (37) it results:

It is worth noting that the derived values are purely theoretical because further reduction can be derived by applying full (36). Moreover, a typical cruise engine status was assumed. In other conditions, the level of emissions can increase or decrease.
In summary, acoustic sensors are capable of determining
a rough estimate of object bearing, and their detection performance can be poor depending on the type of engine and environmental condition. In general, several directional microphones
can be installed in strap-down configuration on the aircraft fuselage pointing toward a specific boresight. If an object is detected
by that sensor, the aircraft has to maneuver towards a direction
that prevents a collision with an aircraft incoming from the boresight of the microphone that has performed the detection. As a
consequence, they are not considered a primary source of reference for SAA but can be a low-cost option as auxiliary source
[27, 28].
  Airborne EO cameras:  EO cameras are passive imaging sensors that operate in the visible and IR wavelengths. Imaging sensors are formed by rectangular arrays of detectors that are capable
of acquiring the visible intensity of light over a large solid angle
when placed in the focal plane of a proper lens system. Each detector in the array is called a pixel. The extent of the solid angle is
called the sensors' FOV. If f is the focal length of the lens system
and d is the size in one direction of the whole detector array the
angular dimension Δθ of the FOV in the same direction is given
by (38), such as:
	(38)
If n detectors are uniformly distributed along that direction, each
one is capable of estimating the average intensity incoming from a
region having angular aperture

IEEE A&E SYSTEMS MAGAZINE	

. Δα is called the instanNOVEMBER 2016, Part II of II



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