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Two-Dimensional Data Conversion for One-Dimensional Adaptive Noise Canceler in Low Frequency SAR Change Detection
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.ORCID iD: 0000-0002-6643-312x
SAAB Surveillance, SWE.
SAAB Surveillance, SWE.
2018 (English)In: IEEE Transactions on Aerospace and Electronic Systems, ISSN 0018-9251, E-ISSN 1557-9603, Vol. 54, no 5, p. 2611-2618Article in journal (Refereed) Published
Abstract [en]

One-dimensional (1-D) adaptive noise canceler (ANC) has been used for false alarm reduction in low frequency SAR change detection. The paper presents possibilities to process two-dimensional (2-D) data by an 1-D ANC. Beside concatenating the rows of 2-D data in a matrix form to convert it to 1-D data in a vector form, two conversion approaches are considered: concatenating the columns of 2-D data and local concatenation, i.e., the conversion to 1-D is performed locally on each block of the 2-D data. A ground object can occupy more than one row and/or more than one column of 2-D data. In addition, the properties in cross-range and range of an image are not the same. Thus, different conversion approaches may lead to different performance of an 1-D ANC and hence different change detection results. Among the considered approaches, the local concatenating approach is shown to provide slightly better performance in terms of probability of detection and false alarm rate. IEEE

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2018. Vol. 54, no 5, p. 2611-2618
Keywords [en]
Adaptive signal processing, ANC, Azimuth, change detection, Frequency conversion, Matrix converters, Noise measurement, SAR, statistics, Synthetic aperture radar, Wires, Chemical detection, Errors, Matrix algebra, Optical frequency conversion, Signal processing, Spurious signal noise, Wire, Adaptive noise cancelers, False alarm reductions, Noise measurements, Probability of detection, Two Dimensional (2 D), Data handling
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:bth-17002DOI: 10.1109/TAES.2018.2866742ISI: 000447045700039Scopus ID: 2-s2.0-85052685958OAI: oai:DiVA.org:bth-17002DiVA, id: diva2:1247921
Funder
Knowledge FoundationAvailable from: 2018-09-13 Created: 2018-09-13 Last updated: 2018-10-30Bibliographically approved

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Vu, Viet ThuyPettersson, Mats

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