This paper deals with the problem of detecting a collision target in ground clutter, using a long integration time. A single reception channel being available, classical space time adaptive processing (STAP) cannot be used. After range processing, ground clutter can be modeled as a known interference subspace in the Doppler domain depending on its radial and orthoradial speeds. We exploit this ...

Subspace recycling iterative methods and other subspace augmentation schemes are a successful extension to Krylov in which is augmented with fixed spanned by vectors deemed be helpful accelerating convergence or conveying knowledge of the solution. Recently, survey was published, framework describing vast majority such proposed [Soodhalter et al., GAMM-Mitt., 43 (2020), Art. e202000016]. In man...

In this paper, we study the matrix denoising model $Y=S+X$, where $S$ is a low rank deterministic signal and $X$ random noise matrix, both are $M\times n$. scenario that $M$ $n$ comparably large signals supercritical, fluctuation of outlier singular vectors $Y$, under fully general assumptions on structure distribution $X$. More specifically, derive limiting angles between principal $Y$ their c...

Cocktail-party Problems (increasing generality): • Independent component analysis (ICA) [1, 2]: onedimensional sound sources. • Independent subspace analysis (ISA) [3]: independent groups of people. • Blind source deconvolution (BSD) [4]: one-dimensional sound sources and echoic room. • Blind subspace deconvolution (BSSD) [5]: independent source groups and echoes. Separation Theorem: • ISA ([3]...

Preconditioning  Krylov Subspace Methods are commonly used for solving linear system  Standard implementations are communication-bound due to required SpMV and orthogonalization in every iteration  Solution: rearrange algorithms to perform s iterations at a time without communicating (s-step methods)  SpMV in each iteration is replaced with a call to the Matrix Powers Kernel, which performs...

A new signal subspace approach for sinusoidal parameter estimation of multiple tones is proposed in this paper. Our main ideas are to stack the observed data into a matrix without reuse of elements and exploit the principal singular vectors of this matrix for parameter estimation. Comparing with the conventional subspace methods which employ Hankel-style matrices with redundant entries, the pro...

We present a new motion segmentation algorithm: the Enhanced Local Subspace Affinity (ELSA). Unlike Local Subspace Affinity, ELSA is robust in a variety of conditions even without manual tuning of its parameters. This result is achieved thanks to two improvements. The first is a new model selection technique for the estimation of the trajectory matrix rank. The second is an estimation of the nu...