IEEE - Aerospace and Electronic Systems - November 2019 - 3

RF SENSING TECHNOLOGIES FOR ASSISTED DAILY LIVING IN HEALTHCARE:
A COMPREHENSIVE REVIEW
The aim of radio-frequency (RF) sensing for assisted living is to deliver automatic support
and monitoring for older people in their homes, impaired patients living independently,
individuals in need of continuous support, and people suffering from chronic diseases
that require them to stay in care-homes or at hospitals. RF sensing technologies have the
potential to improve the quality of living of elderly people or disabled individuals in need
of timely assistance. This paper provides a comprehensive review on three of the most
innovative RF sensing technologies for activities of daily living in healthcare sector
(namely active radar, passive radar, and wireless channel information and RFID sensing)
and presents some of the open challenges that need to be addressed.

DEEP LEARNING FOR CLASSIFICATION OF MINI-UAVS USING
MICRO-DOPPLER SPECTROGRAMS IN COGNITIVE RADAR
Target recognition using micro-Doppler spectrograms measured with radar has many benefits when compared with optical target recognition due to the all-weather and day-andnight capability of radar. Micro-Doppler spectrograms are, however, difficult to interpret
by radar operators. Consequently, there is a need for automatic target recognition methods
for radar. Cognitive radars that learn to extract relevant features from measured or simulated micro-Doppler spectrograms stored in long-term memory, offer the potential to automatically recognize targets. In this paper, the ability of various deep learning techniques,
such as convolutional neural networks and recurrent neural networks for the classification
of mini-UAVs using micro-Doppler spectrograms is investigated. In addition, the detection of spectrograms from targets that are not known by the cognitive radar, denoising of
spectrograms, and the generation of spectrograms for underrepresented target classes with
generative adversarial networks is explored.

SAFETY ASSESSMENT PROCESS OPTIMIZATION FOR INTEGRATED MODULAR
AVIONICS
In order to evaluate the safety impacts introduced by the additional interactions between
the software partition and the integrated modular avionics platform, an optimized safety
assessment process is proposed to address the software partition specific failure mode,
quantitative failure rate budget allocation, software reliability verification, and feedback to
higher level safety assessment. With a case study based on an airborne datalink system, the
optimized safety assessment process is discussed in detail, including the specific failure
condition and corresponding preventive/corrective actions, the allocation and verification
of software partition failure rate, as well as the feedback channel of these partition software
failure rate to item/function failure mode and effect assessment. A reliability framework
of partition software is also presented to support the reliability verification of partition
software. The methodology is applicable to other IMA-based avionics system.

NOVEMBER 2019

IEEE A&E SYSTEMS MAGAZINE

3
IEEE - Aerospace and Electronic Systems - November 2019

Table of Contents for the Digital Edition of IEEE - Aerospace and Electronic Systems - November 2019
