TSP Volume 67 Issue 6

Two-dimensional (2-D) spectrum sensing is addressed in the context of a cognitive radar to gather real-time space-frequency electromagnetic awareness. Assuming a sensor equipped with multiple receive antennas, a discrete-time sensing signal model formally accounting for multiple snapshots of observations is introduced.

Beamforming is an attractive technique to improve the system performance for multi-input multi-output (MIMO) communications. Previous works mainly focus on improving the data transmission quality. However, the potential of beamforming for improving the localization quality is not yet fully studied.

We propose two-channel critically-sampled filter banks for signals on undirected graphs that utilize spectral domain sampling. Unlike conventional approaches based on vertex domain sampling, our transforms have the following desirable properties.

We present our results of applying wavelet theory to the classic problem of estimating the unknown parameters of a model function subject to noise. The model function studied in this context is a generalization of the second-order Gaussian derivative of which the Gaussian function is a special case.