18,552 research outputs found
Knowledge-Aided STAP Using Low Rank and Geometry Properties
This paper presents knowledge-aided space-time adaptive processing (KA-STAP)
algorithms that exploit the low-rank dominant clutter and the array geometry
properties (LRGP) for airborne radar applications. The core idea is to exploit
the fact that the clutter subspace is only determined by the space-time
steering vectors,
{red}{where the Gram-Schmidt orthogonalization approach is employed to
compute the clutter subspace. Specifically, for a side-looking uniformly spaced
linear array, the} algorithm firstly selects a group of linearly independent
space-time steering vectors using LRGP that can represent the clutter subspace.
By performing the Gram-Schmidt orthogonalization procedure, the orthogonal
bases of the clutter subspace are obtained, followed by two approaches to
compute the STAP filter weights. To overcome the performance degradation caused
by the non-ideal effects, a KA-STAP algorithm that combines the covariance
matrix taper (CMT) is proposed. For practical applications, a reduced-dimension
version of the proposed KA-STAP algorithm is also developed. The simulation
results illustrate the effectiveness of our proposed algorithms, and show that
the proposed algorithms converge rapidly and provide a SINR improvement over
existing methods when using a very small number of snapshots.Comment: 16 figures, 12 pages. IEEE Transactions on Aerospace and Electronic
Systems, 201
Asymmetric Protocols for Scalable High-Rate Measurement-Device-Independent Quantum Key Distribution Networks
Measurement-device-independent quantum key distribution (MDI-QKD) can
eliminate detector side channels and prevent all attacks on detectors. The
future of MDI-QKD is a quantum network that provides service to many users over
untrusted relay nodes. In a real quantum network, the losses of various
channels are different and users are added and deleted over time. To adapt to
these features, we propose a type of protocols that allow users to
independently choose their optimal intensity settings to compensate for
different channel losses. Such protocol enables a scalable high-rate MDI-QKD
network that can easily be applied for channels of different losses and allows
users to be dynamically added/deleted at any time without affecting the
performance of existing users.Comment: Changed the title to better represent the generality of our method,
and added more discussions on its application to alternative protocols (in
Sec. II, the new Table II, and Appendix E with new Fig. 9). Added more
conceptual explanations in Sec. II on the difference between X and Z bases in
MDI-QKD. Added additional discussions on security of the scheme in Sec. II
and Appendix
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