Aerospace and Electronic Systems Magazine November 2016 Tutorial X - 99


Fasano et al.
taneous field of view (IFOV) of the sensor in the above mentioned
direction, i.e., the angular width of a pixel. Given the array arrangement of detectors, each sensor has a vertical and a horizontal
FOV and IFOV.
Systems operating in the visible wavelengths, i.e., λ ∈
[400 nm...700 nm], exploit the reflection of the sunlight by objects
at daytime. Two types of technologies are available to realize visible wavelength sensor arrays:
1.	 charge couple devices (CCD) that are older systems that have
better detector SNR but are more difficult to integrate with current processing electronics
2.	 active pixel sensors (APS) realized with complementary metal-oxide-semiconductor (CMOS) technology that have worse
SNR but are better integrated with current processing electronics. Moreover, they are capable to perform nondestructive
readout of detectors, i.e., the level of light intensity can be read
but the sensor keeps collecting charges. This permits local
amplification of zones that are badly illuminated but prevents
other detectors to saturate.
Visible cameras also output information about the color of a
pixel by applying a proper Bayer filter in front of the array. Even if
the knowledge of object color can be useful for object recognition,
it is not needed to assess the object position. Moreover, the Bayer
filter reduces the SNR of a sensor. For this reason, panchromatic
cameras are usually preferred to color ones.

Fig. 15.

Signal processing sequence for EO cameras.

allows angular pixel size up to 0.01°. Conversely, the largest
MWIR camera has 640 pixels per line. For the same FOV reported for the case of visible and NIR, the configuration of MWIR
determines an angular pixel size of 0.08°, i.e., almost one order
of magnitude worse. In addition, MWIR cameras have typically
worse noise levels. These drawbacks determine a reduced performance for SAA applications even if the use of MWIR cameras would have been appealing in order to support nighttime
operations.
If an object is detected on a line at a distance of q pixels from
the pixel that is aligned with the boresight axis and d/n is the size
of a single detector in the array, its angular span γ can be computed
by means of (39):
	(39)

Two types of IR sensors are available:
1.	 near IR sensors (NIR) that operate in the range of wavelengths
λ ϵ [750 nm...1400 nm]. They are essentially used to enhance
the vision in poorly illuminated conditions. Their detectors are
CCD without coating filters so that they collect light and noise
over a wide range of frequencies. These sensors benefit from
the relatively large quantity of energy emitted by artificial illumination sources in the NIR wavelength. For instance, these
sensors are used to realize night goggles.
2.	 thermal IR sensors medium and long wave IR (MWIR
and LWIR) that operate in the ranges of wavelengths λ ϵ
[3000 nm...8000 nm](MWIR) and λ ϵ [8000 nm...15000 nm]
(LWIR). Their detectors are called micro-bolometers and they
need forced cooling in order to keep the level of noise at a reasonable value. Essentially, they detect the heat emission from
engines and the plume exhaust because in these wavelengths
there is the peak of the blackbody radiation curves. In particular, MWIR permits bright images of hot objects with the adoption of compact cameras.
Resolution of EO cameras is defined as the minimum distance
between targets that can be resolved as different. Obviously, it is
related to geometric pixel size (i.e., the IFOV) but depends on lens
characteristics, system noise, and illumination conditions. The blur
effect due to motion, of both target and own aircraft, should be
taken into account. As a general rule of thumb, a resolution no better than 1.5-2 IFOVs should be assumed.
Visible and NIR CCD and CMOS can have up to 5000 pixels
per line. Over a FOV of 50°, the above reported configuration
NOVEMBER 2016, Part II of II	

In case the direction of the line in the array is vertical, (39) permits
the estimation of the object elevation with respect to sensor axis.
Instead, for horizontal lines, (39) gives the object azimuth.
The whole process that leads to the determination of the
object LOS is reported in Fig. 15. While readout, i.e., the process to transform the two-dimensional signal in the array into
a one-dimensional stream, and analog to digital (A/D) conversion are performed by electronics embedded in the detector,
the image processing depends on the type of application. First
of all, the type of processing applied for SAA application is
different for image regions located above or below the line
of horizon. Indeed, the distribution of intensities above the
horizon tends to be much more uniform than the one of pixels
located below the horizon. This determines different SNR levels to detect the same object with similar visibility and illumination conditions. If the object is located above the horizon,
the SNR tends to be higher than the case of an object located
below the horizon.
Regarding the type of image processing technique adopted,
several solutions are available, such as [29] the following.
1.	 Basic edge detection. This technique highlights the pixels that
are located in regions that have sudden changes of intensity.
Since an object of interest tends to be brighter or darker than
its background, the edge detection process will likely highlight
its boundary pixels. A drawback of this simple technique is
the high number of false alarms that can be generated unless a
proper thresholding strategy is adopted. This technique can be
useful in case EO cameras are used as a secondary sensor to a

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