2019
DOI: 10.1109/access.2019.2953065
|View full text |Cite
|
Sign up to set email alerts
|

Improved Intra-Pulse Modulation Phase Calibration Algorithm With Accelerated Entropy Minimization Optimization

Abstract: Intra-pulse modulation phase calibration is necessary in inverse synthetic aperture radar (ISAR) imaging of high-speed targets. Traditional intra-pulse phase error compensation strategies rarely handle the high-order and slow-time-variant phase components induced during the coherent processing interval. In this paper, a novel intra-pulse modulation phase calibration with a two-dimensional (2-D) parametric phase model is proposed. It models the intra-pulse phase errors as a 2-D time-variant polynomial with acco… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
5
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
2
1

Relationship

1
2

Authors

Journals

citations
Cited by 3 publications
(5 citation statements)
references
References 33 publications
0
5
0
Order By: Relevance
“…Raw numbers and waveforms generated during biofeedback have little inherent meaning to the typical user. As such, evidence‐based user experience recommends that an app translate a score into simple color‐coded categories to delineate a low versus a high score (Lu et al., 2019). However, categorization without personalization risks algorithmic inequity.…”
Section: Discussionmentioning
confidence: 99%
See 2 more Smart Citations
“…Raw numbers and waveforms generated during biofeedback have little inherent meaning to the typical user. As such, evidence‐based user experience recommends that an app translate a score into simple color‐coded categories to delineate a low versus a high score (Lu et al., 2019). However, categorization without personalization risks algorithmic inequity.…”
Section: Discussionmentioning
confidence: 99%
“…Using Kubios as a guideline, data cleaning was automated using real-time filtering algorithms to interpolate missing data and remove global outliers, ectopic beats (using a modified Kamanth filter), and movement artifacts (Tarvainen et al, 2014). Next, we applied a rolling window application of a time-bounded Levenberg-Marquardt (LM) algorithm for nonlinear curve-fitting (Aschbacher et al, 2023;Brown & Dennis, 1971;Gavin, 2022;Lu et al, 2019), which utilized a sine function to fit four parameters: amplitude, omega (angular frequency), phase, and the mean heart rate.…”
Section: Algorithm For Real-time Hrvb Amplitudementioning
confidence: 99%
See 1 more Smart Citation
“…Since the target’s size is much smaller than the distance between the target and radar, the electromagnetic wave irradiated on the target can be regarded as a plane wave. According to the turntable model of the ISAR imaging [25], [26], the target coordinate can be established near the radar on the radar imaging plane. Assume the target coordinate is represented by ()Xtg,Ytg $\left({X}_{tg},{Y}_{tg}\right)$.…”
Section: The Proposed False‐target Jamming Methodsmentioning
confidence: 99%
“…To compute the magnitude of respiration-related HRV oscillations in real-time, the app applied a non-linear curve-fitting algorithm (bounded Levenberg-Marquardt (LM) algorithm with the ml-levenberg-marquardt package; https://github.com/mljs/levenberg-marquardt) implemented in JavaScript (Brown & Dennis, 1971;Gavin, 2022;Lu et al, 2019). The algorithm was performed on rolling windows of 30-seconds of data (Aschbacher, 2022).…”
Section: Hrvb Amplitudementioning
confidence: 99%