Compressive Shift Retrieval
2013 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, 6034-6038 p.Article in journal (Refereed) Published
The classical shift retrieval problem considers two signals in vector form that are related by a shift. This problem is of great importance in many applications and is typically solved by maximizing the cross-correlation between the two signals. Inspired by compressive sensing, in this paper, we seek to estimate the shift directly from compressed signals. We show that under certain conditions, the shift can be recovered using fewer samples and less computation compared to the classical setup. We also illustrate the concept of superresolution for shift retrieval. Of particular interest is shift estimation from Fourier coefficients. We show that under rather mild conditions only one Fourier coefficient suffices to recover the true shift.
Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2013. 6034-6038 p.
Parameter estimation; compressed sensing; signal processing algorithms; signal sampling
Electrical Engineering, Electronic Engineering, Information Engineering
IdentifiersURN: urn:nbn:se:liu:diva-110701DOI: 10.1109/ICASSP.2013.6638823ISI: 000340845200006OAI: oai:DiVA.org:liu-110701DiVA: diva2:749237
Funding Agencies|Swedish Research Council in the Linnaeus center CADICS; European Research Council ; Sweden-America Foundation; Swedish Research Council; FORCES (Foundations Of Resilient CybEr-physical Systems) - NSF [CNS-1239166]; Israel Science Foundation [170/10]; SRC; Intel Collaborative Research Institute for Computational Intelligence (ICRI-CI); Ollendorf Foundation; ARO [63092-MA-II]; DARPA [FA8650-11-1-7153]; ONR [N00014-13-1-0341]2014-09-232014-09-192014-12-02