“Things I should have put in the book” with Brian Watson

Author Brian Watson’s book, Non-Line-of-Sight-Radar, wrote a comprehensive volume, but there’s always more to talk about. Read on for his thoughts on radar, how he wrote the book, and his writing process:

Radar: Big data is being incorporated into a variety of fields to improve performance including medicine, physics, and smart systems. Radar is no exception to this trend. We can improve radar tracking using knowledge of the building geometries and predicting the (multipath) reflections back to the radar receiver. In an urban environment, multipath can be severe with several bounces between the radar and target (see below). Even the absence of a signal can provide information about a target’s location.

Example of severe multipath environment with multiple radar bounces from buildings between a radar (green box) and target (red square) (image produced by Steve McNeil and Dave Kirk, Information Systems Laboratories Inc. using Wireless InsiteTM, 2010).

The book, NLOS Radar, details several methods for generating a digital city map and simulating multipath for an assumed emitter / receiver geometry. One interesting way to generate a city map is to capture buildings from Google EarthTM. Unfortunately, Google Earth doesn’t have a way to directly export city geometries. But you can generate 3-D models in a commercial photogrammetry program such as pix4DTM using multiple screenshots of a single building or set of buildings. In Chapter 4, we demonstrate generation of a 3-D model. Unfortunately I picked a rather boring condominium in Chicago. After the book was published I realized I should have used a more recognizable and detailed landmark such as the one shown below. From a set (22) of screenshots, I produced a 3-D texture model of the Shedd Aquarium in Chicago. FYI – I tend to pick Chicago landmarks since I was born and raised on the South Side.

 A 3-D rotatable model of the Shedd Aquarium in Chicago Produced using Pix4D: Point cloud with camera locations.  3-D topography map. 3-D texture map.

Personal Motivations: I was a always drawn to science. For my eighth grade science fair, I built a simple talking computer before such things were common. I grew up in Chicago in a family that does not appreciate science and/or education. They believe that football, beer, and deep dish pizza represent the epitome of culture. As a child, I was building model airplanes, electronic gadgets, and spending time in the local library. So when I pursued a Ph.D. in physics, no one was surprised.

I had two great high school teachers that inspired my career choices. The first was Dr. Joseph Miller, who started a magnet school near Chicago called Project Individual Education (P.I.E.). He worked in the Peace Corps for several years in his youth. He conducted his life in a way that I believe all people should strive to emulate. He passed up higher paying opportunities to try to make the world a better place. My math teacher, Dr. Skinner, was a talented educator that made calculus seem obvious. He had an experiment on the Space Shuttle, Challenger, in 1986 and was devastated after the disastrous launch.

I would also like to thank my stunningly beautiful wife who listened to my nerd talk every day and supports my writing projects.

Writing Process: There is a book entitled “Deep Work” by Cal Newport, which really resonated with me. I have a weird ability to focus on one thing for several hours. I get into a kind of transcendental mental state that allows me to write efficiently or to solve difficult problems. I sort of assumed that I was unique. Most people experience fairly distracted lives with a lot of mental clutter. With the advent of social media and constant communication via text and e-mail, the situation has only gotten worse. But I was surprised to learn that many people use this kind of mental state in a variety of fields to produce deep work. I can’t always get into this mode when interruptions are frequent. On those days, I try to work on less demanding tasks so that I’m not wasting time.

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