Joint Space-(Slow) Time Transmission With Unimodular Waveforms and Receive Adaptive Filter Design for Radar

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review


Research units


A novel computationally efficient method for jointly designing the space-(slow) time (SST) transmission with unimodular waveforms and receive adaptive filter is developed for different radar configurations. The range sidelobe effect and Doppler characteristics are considered. In particular, we develop a novel approach for jointly synthesizing unimodular SST waveforms and minimum variance distortionless response receive adaptive filter for two cases of known Doppler information and presence of uncertainties on clutter bins. Corresponding non-convex optimization problems are formulated and efficient algorithms are derived. The main ideas of the algorithm developments are to decouple composite objective function of the formulated problems, generate minorizing surrogates, and then solve the joint design problem iteratively, but in closed form for each iteration by means of minorization-maximization technique. The proposed algorithms demonstrate good performance and have fast convergence speed and low complexity.


Original languageEnglish
Title of host publication2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Publication statusPublished - 2018
MoE publication typeA4 Article in a conference publication
EventIEEE International Conference on Acoustics, Speech, and Signal Processing - Calgary, Canada
Duration: 15 Apr 201820 Apr 2018

Publication series

NameProceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing
ISSN (Electronic)2379-190X


ConferenceIEEE International Conference on Acoustics, Speech, and Signal Processing
Abbreviated titleICASSP
Internet address

    Research areas

  • Adaptive filter, joint waveform design, radar, minorization-maximization, space-(slow) time

Download statistics

No data available

ID: 19264417