We consider the problem of target localization by a
network of passive sensors. When an unknown target emits an
acoustic or a radio signal, its position can be localized with multiple
sensors using the time difference of arrival (TDOA) information.
In this paper, we consider the maximum likelihood formulation
of this target localization problem and provide efficient convex
relaxations for this nonconvex optimization problem.We also propose
a formulation for robust target localization in the presence of
sensor location errors. Two Cramer-Rao bounds are derived corresponding
to situations with and without sensor node location errors.
Simulation results confirm the efficiency and superior performance
of the convex relaxation approach as compared to the
existing least squares based approach when large sensor node location
errors are present.
DESCRIPTION
The Texas Instruments MSP430 family of ultra-low-power microcontrollers consists of several devices featuring
different sets of peripherals targeted for various applications. The architecture, combined with five low-power
modes, is optimized to achieve extended battery life in portable measurement applications. The device features a
powerful 16-bit RISC CPU, 16-bit registers, and constant generators that contribute to maximum code efficiency.
The digitally controlled oscillator (DCO) allows wake-up from low-power modes to active mode in less than 1 μs.
The MSP430G2x13 and MSP430G2x53 series are ultra-low-power mixed signal microcontrollers with built-in 16-
bit timers, up to 24 I/O capacitive-touch enabled pins, a versatile analog comparator, and built-in communication
capability using the universal serial communication interface. In addition the MSP430G2x53 family members
have a 10-bit analog-to-digital (A/D) converter. For configuration details see Table 1.
Typical applications include low-cost sensor systems that capture analog signals, convert them to digital values,
and then process the data for display or for transmission to a host system.
The concept of smart cities emerged few years ago as a new vision for urban
development that aims to integrate multiple information and communication
technology (ICT) solutions in a secure fashion to manage a city’s assets. Modern ICT
infrastructure and e-services should fuel sustainable growth and quality of life,
enabled by a wise and participative management of natural resources to be ensured
by citizens and government. The need to build smart cities became a requirement that
relies on urban development that should take charge of the new infrastructures for
smart cities (broadband infrastructures, wireless sensor networks, Internet-based
networked applications, open data and open platforms) and provide various smart
services and enablers in various domains including healthcare, energy, education,
environmental management, transportation, mobility and public safety.
The Internet of Things is considered to be the next big opportunity, and challenge, for the
Internet engineering community, users of technology, companies and society as a whole. It
involves connecting embedded devices such as sensors, home appliances, weather stations
and even toys to Internet Protocol (IP) based networks. The number of IP-enabled embedded
devices is increasing rapidly, and although hard to estimate, will surely outnumber the
number of personal computers (PCs) and servers in the future. With the advances made over
the past decade in microcontroller,low-power radio, battery and microelectronic technology,
the trend in the industry is for smart embedded devices (called smart objects) to become
IP-enabled, and an integral part of the latest services on the Internet. These services are no
longer cyber, just including data created by humans, but are to become very connected to the
physical world around us by including sensor data, the monitoring and control of machines,
and other kinds of physical context. We call this latest frontier of the Internet, consisting of
wireless low-power embedded devices, the Wireless Embedded Internet. Applications that
this new frontier of the Internet enable are critical to the sustainability, efficiency and safety
of society and include home and building automation, healthcare, energy efficiency, smart
grids and environmental monitoring to name just a few.
This chapter introduces concepts on cooperating objects and wireless sensor net-
works that will be used in the following chapters. It also introduces the Embedded
WiSeNts Coordination Action. Finally, it presents an overview of the book and the
relations between the following chapters.
