About

Assistant Professor Jose Angel Martinez-Lorenzo is involved in research related to millimeter wave (mmWave) communications, which are a key component of 5G networks and future Internet of Things (IoT) devices. His work includes developing a programmable mmWave 60-GHz testbed that features modular hardware and software architectures to enable rapid prototyping of user-defined designs. The testbed is equipped with high-performance computational capacity to support real-time data processing, and it can generate high-quality RF signals essential for channel sounding and communications prototyping. His research aims to address the challenges of building complete mmWave communication prototypes, supporting research from theoretical physical-layer schemes to practical, real-world performance evaluation in mesh networked systems. This work contributes to advancing the capabilities of wireless communication systems, particularly in the context of high data rates, low latency, and scalable network architectures.

Research topics

• Computer Science
• Telecommunications
• Acoustics
• Physics
• Materials science
• Optics
• Optoelectronics
• Mathematics

Selected publications

• PX4 Simulation Results of a Quadcopter with a Disturbance-Observer-Based and PSO-Optimized Sliding Mode Surface Controller

  Drones · 2022 · 22 citations

  • Computer Science
  • Control engineering
  • Computer Science

  This work designed a disturbance-observer-based nonlinear sliding mode surface controller (SMC) and validated the controller using a simulated PX4-conducted quadcopter. To achieve this goal, this research (1) developed a dynamic mathematical model; (2) built a PX4-based simulated UAV following the model-based design process; (3) developed appropriate sliding mode control laws for each degree of freedom; (4) implemented disturbance observers on the proposed SMC controller to achieve finer disturbance rejection such as crosswind effect and other mutational disturbances; (5) optimized the SMC controller’s parameters based on particle swarm optimization (PSO) method; and (6) evaluated and compared the quadcopter’s tracking performance under a range of noise and disturbances. Comparisons of PID control strategies against the SMC were documented under the same conditions. Consequently, the SMC controller with disturbance observer facilitates accurate and fast UAV adaptation in uncertain dynamic environments.

  DOI

• Microwave-Induced Thermoacoustic Compressive Imaging With Metamaterial Coding

  2021 · 1 citations

  Senior authorCorresponding
  • Computer Science
  • Acoustics
  • Materials science
  DOI

• Microwave Induced Thermoacoustic Imaging With Multi-Pulse in Geological Application

  2021

  Senior authorCorresponding
  • Computer Science
  • Acoustics
  • Physics
  DOI

Frequent coauthors

• Ashkan Ghanbarzadeh-Dagheyan

  University of Twente

  4 shared

• Ali Molaei

  4 shared

• Aida Kuri Martinez

  Harvard Vanguard Medical Associates

  3 shared

• Richard Obermeier

  Northeastern University

  3 shared

• Chang Liu

  Anhui University of Technology

  3 shared

• Xu Mao

  Qinghai Red Cross Hospital

  2 shared

• Juan Heredia-Juesas

  Northeastern University

  2 shared

• Andrew J. Westwood

  2 shared

Labs

• Sensing, Imaging, Control, and Actuation LaboratoryPI

Awards & honors

• Best Paper Award on the 2012 IEEE Homeland Security Technolo…
• First prize on the 2012 National Security Innovation Competi…
• Paper featured in the cover page: 'DIRECT: deterministic rad…
• Paper featured in the cover page: 'ICARA: Induced Current An…
• NSF CAREER: 4D mm-Wave Compressive Sensing and Imaging at On…

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