Signal Processing Laboratory - LPS
Escola Politécnica da USP   Adaptive Filtering and Estimation Group



The following is a short description of our current research:

    1. Low-cost algorithms for parameter estimation

This line of research is funded by FAPESP (São Paulo State Research Council).  Part of the work is in collaboration with Prof. Yuriy V. Zakharov, from the University of York, and Prof. Rodrigo de Lamare, from PUC-Rio and the University of York.

This project is concerned with the study and development of low-cost algorithms for parameter estimation, such as adaptive filters, with particular interest in algorithms for sparse identification.

We are studying new ways of using prior information to improve estimation methods, especially for on-line (adaptive) estimation.  Prior information may be related to, for example,
  • sparsity
  • maximum bounds (box-constraints)
  • smoothness
  • dynamical models for parameter variation

The use of prior information usually leads to algorithms that use the available data more efficiently (for example, obtaining good estimates with less data).  Our work involves the development of new algorithms, of new theoretical tools for analysis and design, and procedures and structures for actual implementation in hardware (DSPs or FGPAs) or software.

    2. Efficient algorithms for array processing

This project, also funded by FAPESP, is geared towards the development of low-complexity algorithms for array processing, in applications such as beamforming and acoustic image estimation.  Much of the work revolves around the Kronecker Array Transform (KAT), proposed in our lab, which is a method that allows a substantial reduction in the number of arithmetic operations in beamforming.  We have built microphone arrays to use the new transform in acoustic image estimation, and are actively working on further improving the KAT, designing and building new microphone arrays, extending the results to new applications, such as synthetic aperture radar, and developing better mathematical tools to understand the performance of the new methods.

   Acoustic image obtained with delay-and-sum beamforming.  Left: 42-microphone array; right: 61-microphone array.  The source is a single loudspeaker, and strong echo from the ground.Acoustic image
                      - single loudspeaker with ground echo. Obtained
                      with a 42 (left) and 61 (right) microphone array,
                      using delay-and-sum beamforming.

Acoustic image obtained with same data as before, but using total variation regularization.  Left: 42-microphone array; right: 61-microphone array.
Acoustic image - single
                  loudspeaker with ground echo. Obtained with a 42
                  (left) and 61 (right) microphone array, using
                  optimization with total variation regularization.

    3. Structural health monitoring

This project is funded by EMBRAER, and aims to improve existing methods, and develop new methods for localization and classification of defects in mechanical structures.

Sensor network monitoring
                  aircraft structure.

PSI - Escola Politécnica - USP
Av. Prof. Luciano Gualberto, trav. 3, n. 158
CEP 05508-970 - São Paulo - SP - Brazil