3 research outputs found
Spatial Signature Estimation with an Uncalibrated Uniform Linear Array
In this paper, the problem of spatial signature estimation using a uniform linear array (ULA) with unknown sensor gain and phase errors is considered. As is well known, the directions-of-arrival (DOAs) can only be determined within an unknown rotational angle in this array model. However, the phase ambiguity has no impact on the identification of the spatial signature. Two auto-calibration methods are presented for spatial signature estimation. In our methods, the rotational DOAs and model error parameters are firstly obtained, and the spatial signature is subsequently calculated. The first method extracts two subarrays from the ULA to construct an estimator, and the elements of the array can be used several times in one subarray. The other fully exploits multiple invariances in the interior of the sensor array, and a multidimensional nonlinear problem is formulated. A Gauss–Newton iterative algorithm is applied for solving it. The first method can provide excellent initial inputs for the second one. The effectiveness of the proposed algorithms is demonstrated by several simulation results
Studies on DOA estimation in the presence of multipath in a frequency hopping system
Master'sMASTER OF ENGINEERIN
Planar array design and analysis on direction of arrival estimation for mobile communication systems
The demand of wireless communication has increased significantly in the past few
decades due to huge demand to deliver multimedia content instantly. The expansion
of mobile content paired with affordable mobile devices has opened a new trend for
having access to the latest information on mobile devices. This trend is made
possible by the technology of smart antenna systems as well as array signal
processing algorithms. Array signal processing is not limited to wireless
communication, but also found in other applications such as radar, sonar and
automotive. One of the important components in array signal processing is its ability
to estimate the direction of incoming signals known as directional-of-arrival (DOA).
The performance of DOA algorithms depends on the steering vector since it contains
information about the direction of incoming signals.
One of the main factors to affect the DOA estimation is the array geometries since
the array factor of the array geometries determines the definition of the steering
vector. Another issue in DOA estimation is that the DOA algorithms are designed
based on the ideal assumption that the antenna arrays are free from imperfection
conditions. In practice, ideal conditions are extremely difficult to obtain and thus the
imperfect conditions will severely degraded the performance of DOA estimation.
The imperfect conditions include the presence of mutual coupling between elements
and are also characteristic of directional antenna.
There are three topics being discussed in this thesis. The first topic being investigated
is new geometry of antenna array to improve the performance of DOA estimation.
Two variants of the circular-based array are proposed in this thesis: semi-circular
array and oval array. Another proposed array is Y-bend array, which is a variant of
V-shape array. The proposed arrays are being put forward to offer a better
performance of DOA estimation and have less acquired area compared with the
circular array. It is found out that the semi-circular array has 5.7% better estimation
resolution, 76% lower estimation error, and 20% higher estimation consistency than
the circular array. The oval array improves the estimation resolution by 33%,
estimation error by 60%, and estimation consistency by 20% compared with the
circular array. In addition, for the same number of elements, the oval array requires
12.5% to 15% less area than the circular array. The third proposed array, Y-bend
array, has 23% smaller estimation resolution, 88% lower estimation error, and 7%
higher estimation consistency than the V-shape array. Among the proposed arrays,
the semi-circular possessed the best performance with 25% smaller estimation
resolution, ten times smaller estimation error, and 5% higher estimation consistency
over the other proposed arrays.
Secondly, this thesis investigates the DOA estimation algorithm when using the
directional antenna array. In this case, a new algorithm is proposed in order to suit
the characteristics of the directional antenna array. The proposed algorithm is a
modified version of the Capon algorithm, one of the algorithms in beamforming
category. In elevation angle estimation, the proposed algorithm achieves estimation
resolution up to 1°. The proposed algorithm also manages to improve the estimation
error by 80% and estimation consistency by 10% compared with the Capon
algorithm. In azimuth angle estimation, the proposed algorithm achieves 20 times
lower estimation error and 20% higher estimation consistency than the Capon
algorithm. These simulation results show that the proposed algorithm works
effectively with the directional antenna array.
Finally, the thesis proposes a new method in DOA estimation process for directional
antenna array. The proposed method is achieved by means of modifying covariance
matrix calculation. Simulation results suggest that the proposed method improves the
estimation resolution by 5° and the estimation error by 10% compared with the
conventional method. In summary, this thesis has contributed in three main topics
related to DOA estimation; array geometry design, algorithm for the directional
antenna array, and method in DOA estimation process for the directional antenna
array