Aerospace and Electronic Systems Magazine August 2016 - 39
tial position of the blades. The red box in Figure 1 represents
the iterative procedure steps used to estimate the parameters of
the helicopter, namely the rotation speed, R, the length of the
blades, L, and the number of blades, N. These steps implement
a modified version of the Pruned Orthogonal Matching Pursuit
(POMP) presented in [10], which is the combination of the iterative OMP with a pruning process aimed to solve a parametric
sparse representation problem. Note that the rotation speed of
the main rotor, R, is a distinctive feature of the helicopter, since
it is constant in a normal operational mode [11]. However the
estimate of the length of the blades, L, is not used in the final
classification step, since it is strongly affected by the aspect
angle, thus it does not represent a reliable feature. Finally, the
classification is carried out by finding the entry in a look-up
table that corresponds to the minimum Euclidean distance with
the estimated couple (N;R).
RESULTS
Figure 1.
Block diagram of the proposed classification algorithm.
AUGUST 2016
The algorithm has been tested on both simulated and real data,
the latter acquired in our EM anechoic laboratory environment
using a real scaled helicopter. The simulated dataset is a collection of signals scattered by 9 different helicopters, 100 realizations for each of them. The performance, on varying the SNR
and for each target, is shown in Figure 2. At 0 dB, the percentage of correct classification is equal or greater than 90% for 7
out of 9 targets. The Apache and the Hoplite present the lowest performance: the former is misclassified with the Cobra,
which has a similar rotation speed. For the latter the algorithm
estimates 6 blades rather than 3, which makes it close, in terms
of Euclidean distance, to the Stallion. The validity of the approach is confirmed by the results obtained on the real dataset, which is a collection of signals acquired with a 24 GHz
Continuous Wave (CW) radar and scattered from a two-bladed
helicopter scale model GAUI X3, whose main rotor is made
to rotate at three different speeds. The GAUI X3's main blade
length is 36 cm, which corresponds to a small helicopter, with
blade length of about 290 cm, in a real scenario with an S-band
radar (3 GHz). In order to test the robustness and reliability of
the algorithm, 8 confusers are introduced in the classification
look-up table; the performance shows an overall 82:44% of
correct classification.
IEEE A&E SYSTEMS MAGAZINE
39
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