Statistical Properties of Arcing on GPS Pseudo Random Noise 28

Statistical Properties of Microstructure Noise

We study the estimation of moments and joint moments of microstructure noise. Estimators of arbitrary order of (joint) moments are provided, for which we establish consistency as well as central limit theorems. In particular, we provide estimators of auto-covariances and auto-correlations of the noise. Simulation studies demonstrate excellent performance of our estimators even in the presence o...

Ramsey Properties of Random Subgraphs of Pseudo-Random Graphs

Let G = (V,E) be a d-regular graph of order n. Let Gp be the random subgraph of G for which each edge is selected from E(G) independently at random with probability p. For a fixed graph H, define m(H) := max{e(H ′)/(v(H ′)− 1) : H ′ ⊆ H}. We prove that n(m(H)−1)/m(H)/d is a threshold function for Gp to satisfy Ramsey, induced Ramsey, and canonical Ramsey properties with respect to vertex colori...

Statistical Properties of Random Spin

Calibration of Correlation Radiometers Using Pseudo-Random Noise Signals

The calibration of correlation radiometers, and particularly aperture synthesis interferometric radiometers, is a critical issue to ensure their performance. Current calibration techniques are based on the measurement of the cross-correlation of receivers' outputs when injecting noise from a common noise source requiring a very stable distribution network. For large interferometric radiometers ...

On Pseudo - Random Arrays *

An arrays of O's and l's has the u v horizontal window property if every nonzero view is seen once when a u v window is moved horizontally across the array. We study the problem of constructing an array which, for a given m, has the u x v horizontal window property for all factorizations rn uv. Using maximal linear shift register sequences for the rows we are able to construct such arrays of si...