Information theoretic waveform design with applications to adaptive‐on‐transmit radar

Abstract

The marginal Fisher information (MFI) metric is used to design waveforms for the sake of informationally optimal adaptive‐on‐transmit radar operation. A framework for MFI waveform design is developed and the Polyphase‐Coded FM (PCFM) waveform model is utilised to produce a constant‐modulus, spectrally contained signal amenable to transmission with high‐power amplifiers. The efficacy of the MFI waveform design and minimum mean square error (MMSE) estimation is experimentally demonstrated and extended into an adaptive and dynamic sensing paradigm. The radar transmit waveform is optimised to maximise the Fisher information with respect to the range profile. Upon observing new information from radar echoes, the iterative MMSE (iMMSE) estimator then minimises the estimation error variance according to prior observations. Sequential information maximisation (via waveform design) and error minimisation (via iMMSE) tends towards the Cramér–Rao lower bound (CRLB) with additional measurements improving radar resolution and accuracy. These concepts maximise the information extracted by a radar operating in a congested spectrum where the available bandwidth is limited.

Document Details

Document Type
Pub Defense Publication
Publication Date
Oct 20, 2023
Source ID
10.1049/rsn2.12478

Entities

People

  • Daniel B. Herr
  • James M. Stiles
  • Pranav S. Raju

Organizations

  • Office of Naval Research
  • University of Kansas

Tags

Fields of Study

  • Engineering

Readers

  • Atmospheric Science/Meteorology
  • Statistical inference.
  • Tactical Satellite Communications Systems Engineering.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference