Persymmetric subspace adaptive detection and performance analysis

Adaptive Subspace Target Detection in Hyperspectral Imagery

* Corresponding author. Abstract –Adaptive subspace detectors are widely used for low probability and anomaly detection. The complex remote sensing conditions in which hyperspectral imagery is obtained make the detector performance evaluation a non-trivial task. Many of the detector design parameters can only be studied empirically for their effects on detection performance. In this paper, hype...

Subspace blind adaptive detection for multiuser CDMA

Direct adaptive realizations of the linear minimum mean-square error (MMSE) receiver for direct-sequence code-division multiple access possess the attractive feature of not requiring any explicit information of interference parameters such as timing, amplitudes, or spreading sequences; however, they need a training sequence for the desired user. Recently, a new blind adaptive receiver was propo...

Performance Evaluation and Real-Time Implementation of Subspace, Adaptive, and DFT Algorithms for Multi-tone Detection

We evaluate MUSIC, LMS, and the Goertzel algorithms for dual-tone multiple-frequency estimation. We rate their computational requirements,estimation errors, and their compliance with the CCITT Q.23 and Q.24 standards through MATLAB simulations and real-time implementations on the ADSP-2101 and Motorola 56001 processors.

Subspace-Based Blind Adaptive Multiuser Detection Using Kalman Filter

A new blind adaptive multiuser detection scheme based on a hybrid of Kalman filter and subspace estimation is proposed. It is shown that the detector can be expressed as an anchored signal in the signal subspace and the coefficients can be estimated by the Kalman filter using only the signature waveform and the timing of the desired user. The resulting subspace-based algorithm brings the benefi...

Adaptive paraunitary filter banks for principal and minor subspace analysis