Coupled Fractional Ambiguity Function

The ambiguity function is a vital analytical instrument for characterizing radar waveform attributes, such as time-delay and Doppler resolutions. This paper introduces the coupled fractional ambiguity function (CFrAF), a novel generalization that extends the utility of the classical ambiguity function. We present a theoretical framework for the CFrAF, deriving its fundamental properties such as time-frequency shifts, Moyal’s identity, and the inversion formula. As a consequence of Moyal’s identity, we also establish the maximum and volume properties of the proposed function.

Authors

Institutions

Publication Details

Journal
Istanbul Journal of Mathematics
Published
2026-06-30
DOI
https://doi.org/10.26650/ijmath.2026.00031
Primary Topic
Radar Systems and Signal Processing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Coupled Fractional Ambiguity Function

Ayşe Sandıkçı
Istanbul Journal of Mathematics
Radar Systems and Signal Processing
article

Coupled Fractional Ambiguity Function

Ayşe Sandıkçı
article en

Abstract

The ambiguity function is a vital analytical instrument for characterizing radar waveform attributes, such as time-delay and Doppler resolutions. This paper introduces the coupled fractional ambiguity function (CFrAF), a novel generalization that extends the utility of the classical ambiguity function. We present a theoretical framework for the CFrAF, deriving its fundamental properties such as time-frequency shifts, Moyal’s identity, and the inversion formula. As a consequence of Moyal’s identity, we also establish the maximum and volume properties of the proposed function.

Istanbul Journal of MathematicsVol. 4(1)
Ondokuz Mayıs University (TR)
Reduced inequalities
Openalex Percentile: Top 4%
Radar Systems and Signal Processing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.