Array and Sensor Signal Processing


Content, progress and pedagogy of the module

Learning objectives


  • Must have knowledge about the Cramér-Rao lower bound (CRLB) as well as (asymptotic) optimal unbiased estimators such as minimum variance unbiased estimator, maximum likelihood, and least-squares.
  • Must have knowledge about 1- and 2-dimensional spectral estimation methods such as the period gram, the Yule-Walker equations, subspace-based methods (MUSIC and ESPRIT), and filter-bank methods (Capon’s method and Amplitude and Phase EStimation (APES)).
  • Must have knowledge about fundamental terms and methods applied for design and analysis of adaptive filter such as Steepest descent, least-mean-square (LMS), normalized LMS (NLMS), affine projections (AP), recursive least-squares (RLS), transient and steady-state performance.
  • Must have knowledge about terms and methods applied for design and analysis of multi-rate signal processing systems, such as Hilbert transform, Noble identities, poly-phase decomposition, commutators, re-sampling, as well as up- and down-sampling.


  • Must be able to compare the estimation performance of unbiased estimators by using the CRLB.
  • Must be able to apply methods and algorithms for parametric and non-parametric spectral estimation on 1- and 2-dimensional signals.
  • Must be able to implement fundamental adaptive filters such as the (normalized) least-mean-square filter, the affine projection filter, and the recursive least-squares filter.
  • Must be able to apply fundamental methods for analysis, design, and implementation of poly-phase filters.


  • Must have competencies in analyzing a given problem which in its solution requires advanced signal processing methodologies and next identify appropriate methods and algorithms to solve the problem.
  • Must have competencies in understanding the strengths and weaknesses of the methods

Type of instruction

As described in the introduction to Chapter 3.



Name of examArray and Sensor Signal Processing
Type of exam
Written or oral exam
AssessmentPassed/Not Passed
Type of gradingInternal examination
Criteria of assessmentAs stated in Joint Programme Regulations

Facts about the module

Danish titleArray- og sensor signalbehandling
Module codeESNSPAK3K1
Module typeCourse
Duration1 semester
Empty-place SchemeYes
Location of the lectureCampus Aalborg
Responsible for the module


Study BoardStudy Board of Electronics and IT
DepartmentDepartment of Electronic Systems
FacultyTechnical Faculty of IT and Design