Passive bistatic radar based on staring radar illuminators of opportunity.

Passive Bistatic Radar (PBR) systems use non-cooperative illuminators of opportunity to detect, localise and track targets. They have attracted considerable research interest in recent years because they can be operated and deployed at a relatively low cost, they are difficult to detect and hence allow covert operations in hostile environments, and they do not require the allocation of an increasingly more congested frequency spectrum. Various analogue and digital communication systems have been studied and exploited as illuminators of opportunity for PBR in recent years. Despite the extensive work carried out on PBR that exploit random communication signals, there has been limited research investigating the use of existing non-cooperative radar systems as illuminators of opportunity. The exploitation of radar signals to achieve passive bistatic detection is attracting as it may offer significant advantages. Because common radar waveforms are deterministic, a reference channel is essentially not required to detect a target. The knowledge of the deterministic waveform allows the passive receiver to be matched with the illuminator of opportunity and thus generate a Doppler map. Radar signals are also designed for detection and provide a large bandwidth, a good compression ratio and hence enhanced range resolution. The work presented in this thesis investigates PBR solutions that exploit nonrandom signals transmitted by non-cooperative staring radar systems. Staring radar offer a constant illumination of the volume under surveillance and, unlike radar systems that deploy a rotating antenna, offer a continuous signal of opportunity. They are very attractive illuminators in particular for short range applications to detect low-RCS and slow-moving targets, such as drones. In this research, a passive radar prototype, capable of operating with and without a reference channel, was developed and detection performance investigated on data collected in a set of experimental trials with the Thales-Aveillant Gamekeeper staring radar. Results show that moving targets, including drones, could be successfully detected with a PBR exploiting radar signals and operating with and without the reference channel

Passive Bistatic Radar Detection Using Non-Stationary Transmitters of Opportunity

<p>3MT presentation at the 2016 Defence and Security Doctoral Symposium.</p><p><br></p><p>Passive Bistatic Radar (PBR) systems use non-cooperative illuminations of opportunity to detect, localise and track targets. They have attracted a lot of interest in recent years because 1) they can be operated and deployed at a relatively low cost 2) they are difficult to detect and hence allow covert operations in a hostile environment and 3) because of the proliferation of illuminators of opportunity.</p><p>Various illuminators of opportunity from analogue signal sources to digital ones, have been studied and exploited in recent years, and these include commercial broadcast systems, cellular base stations and local area networks. </p><p>The aim of this research is to investigate the potential of PBR target detection in the presence of non-random signals emitted by a moving transmitter of opportunity and without the use of a reference channel. Typical transmitters of opportunity could be, for example, satellites carrying a SAR system. This research will include a study of the waveform properties, an assessment of target tracking performance and a set of experimental trials to demonstrate the feasibility of the proposed solution.  </p><div><br></div

Simulating the Effectiveness of an IoT Parcel Alert System for Enhancing Delivery Efficiency and Safety During Covid-19

The Internet of Things (IoT) has revolutionized the way devices communicate and interact with one another. Malaysia has witnessed a substantial increase in online purchasing in recent years. The COVID-19 pandemic and the Malaysian government's mobility control order (MCO) have contributed to the rise in online sales. This circumstance has resulted in a substantial increase in the number of packages that Malaysian delivery firms must manage, producing issues for both homeowners and delivery services. Unattended parcel delivery, parcel loss, and unsuccessful delivery efforts have become widespread. This paper proposes an IoT-based Parcel Delivery Alert System to address the challenges associated with unattended parcel delivery, parcel loss, and failed delivery attempts. The system comprises a parcel safe box that integrates with IoT sensors, such as weight and load sensors, image sensors, and light sensors. The IoT sensors provide real-time information about the delivery status and alert the recipient once the delivery has been made. The system's efficiency and effectiveness were evaluated using the MARS simulator, demonstrating a significant improvement in parcel delivery performance. This paper presents the design, development, and simulation of an IoT-based Parcel Delivery Alert System that can enhance the delivery experience while minimizing delivery-related problems. The paper describes the design and development of the parcel safe box and the eventual evolution of the system. One can acquire access to the safe box by scanning the tracking number on the package's delivery label using a QR code

Empowering smart city governance through decentralized blockchain solutions for security and privacy in IoT communications

This paper highlights the benefits and challenges of smart cities, which leverage technology to offer a wide range of services to citizens. While these services have the potential to greatly improve the quality of life in metropolitan areas, they also raise significant privacy and security concerns. The study emphasizes the need to employ "privacy by design" principles to ensure that personal data is protected throughout the entire lifecycle of data, and data owners have the self-control to manage their data according to their preferences. Smart contracts, built on blockchain technology,offer a secure and transparent way of conducting transactions, particularly in e-governance, and automating processes. By leveraging these technologies, smart cities can address the privacy and security challenges they face while continuing to offer cutting-edge services to their inhabitants. Ultimately, the study emphasizes the importance of a proactive approach to privacy and security in the development and implementation of smart cities

Evaluating the effectiveness of machine learning and computer vision techniques for the early detection of maize plant disease

Monitoring plant growth is a crucial agricultural duty. In addition, the prevention of plant diseases is an essential component of the agricultural infrastructure. This technique must be automated tokeep up with the rising food demand caused by increasingpopulation expansion. This work evaluates this business, specifically the production of maize, which is a significant source of food worldwide. Ensure that Mazie's yields are not damaged is a crucial endeavour. Diseases affecting maize plants, such as Common Rust and Blight, are a significant production deterrent. Toreduce waste and boost production and disease detection efficiencies, the automation of disease detection is a crucial strategy for the agricultural sector. The optimal solution is a self-diagnosing system that employs machine learning and computer vision to distinguish between damaged and healthy plants. The workflow for machine learning consists of data collection, data preprocessing, model selection, model training and testing, and evaluation