ISAR Imaging Based on Multiple Measurement Vector Model Sparse Signal Recovery Algorithm

المؤلف

Feng, Junjie

المصدر

Mathematical Problems in Engineering

العدد

المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-8، 8ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2020-07-13

دولة النشر

مصر

عدد الصفحات

8

التخصصات الرئيسية

هندسة مدنية

الملخص EN

A multiple measurement vector (MMV) model blocks sparse signal recovery.

ISAR imaging algorithm is proposed to improve ISAR imaging quality.

Firstly, the sparse imaging model is built, and block sparse signal recovery algorithm-based MMV model is applied to ISAR imaging.

Then, a negative exponential function is proposed to approximately block L0 norm.

The optimization solution of smoothed function is obtained by constructing a decreasing sequence.

Finally, the correction steps are added to ensure the optimal solution of the block sparse signal along the fastest descent direction.

Several simulations and real data simulation experiments verify the proposed algorithm has advantages in imaging time and quality.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Feng, Junjie. 2020. ISAR Imaging Based on Multiple Measurement Vector Model Sparse Signal Recovery Algorithm. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1193465

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Feng, Junjie. ISAR Imaging Based on Multiple Measurement Vector Model Sparse Signal Recovery Algorithm. Mathematical Problems in Engineering No. 2020 (2020), pp.1-8.
https://search.emarefa.net/detail/BIM-1193465

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Feng, Junjie. ISAR Imaging Based on Multiple Measurement Vector Model Sparse Signal Recovery Algorithm. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1193465

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1193465