NDLI: Case study of the higher-order ambiguity function applied to array element signal estimation for non-linear sensor array fault resiliency

Content Provider	IET Digital Library
Author	Northardt, Tom
Abstract	In many practical applications, sensor array elements fail for a multitude of reasons. They are often simplistically excluded from signal processing to avoid the deleterious effects of including them. However, depending on how many array elements fail, the performance of the array could degrade significantly which can negatively affect core array benefits such as array gain (AG) and spatial spectrum estimation. For naval vessels, failed array elements may not be replaced for a long period of time simply due to cost or maintenance schedules which can leave the array in a degraded state. This work focuses on developing a method to regain some of the lost array performance which can be applied in situ until an appropriate maintenance period. By using a higher-order ambiguity function and basis pursuit de-noising techniques, an algorithm is developed that is shown with simulated data to regain nearly all lost array performance as assessed by AG and spectrum estimate correlation when up to half of the array elements have failed.
Starting Page	1850
Ending Page	1856
Page Count	7
ISSN	17518784
Volume Number	13
e-ISSN	17518792
Issue Number	Issue 10, Oct (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-rsn/13/10
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-rsn.2018.5083
Journal	IET Radar, Sonar & Navigation
Publisher Date	2019-05-28
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Array Element Signal Estimation Array Gain Array Signal Processing Basis Pursuit Denoising Technique Estimation Theory Fault Diagnosis Higher-order Ambiguity Function Naval Vessels Nonlinear Sensor Array Fault Resiliency Signal Denoising Signal Processing Signal Processing And Detection Signal Processing Theory Spatial Spectrum Estimation Statistics
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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