ABSTRACT
In the past few years, numerous researchers have devoted to the research of
discovery, identification and detection of near-space target from all over the world. In
this thesis, by the ESPRIT algorithm and the ESPRIT steering vector cross correlation
algorithm, we proposed the ground-based distributed network detection to achieve the
precise positioning of near-space target in the presence of distributed network detection.
Firstly, several conventional target localization algorithms are introduced and their
performance is analyzed. We take the typical near-space target X-51A into consideration
here, it is obtained the model of the near-space target localization method according to
the study of RCS and Doppler frequency shift of full band.
Then an improved ESPRIT algorithm is proposed for location of near-space target.
The original data received by each ground sub-array is reconstructed "up dimension" in
order to obtain more data and improve the positioning accuracy. The latter matrix is
multiplied by a "dimensionality" matrix without information due to increase of amount
of computation caused by data reconstruction. The simulation is based on the improved
ESPRIT algorithm is used to locate the near-space target.
Moreover, we proposed an improved ESPRIT steering vector cross correlation
algorithm to deal with location of near-space target. Direction of arrival of the target
with relative to each array is calculated directly by using the irrelevant principle of each
signal through the method of matrix reconstruction. This not only avoids the error of the
matching algorithm of the reconstruction, but reduces the increase of the computational
complexity caused by the reconstruction matrix. The simulation is based on the
improved ESPRIT the vector cross correlation algorithm for locating near-space targets.
The error of the target location is analyzed from the perspective of target distance,
signal-to-noise, ratio array element number and array radius based on the improved
ESPRIT algorithm and the improved ESPRIT steering vector cross correlation
algorithm. Finally, comparing the improved ESPRIT algorithm and ESPRIT steering
vector cross correlation algorithm with the two conventional algorithm localization
errors. Then the optimization methods of reducing position error are given under the
same condition, which analyze the difference of the positioning error of near-space
targets in five array forms.
