We choose to go to the moon in this decade and do other thing not because they are easy, because they are hard, because that challenge is one that we are willing to accept, one we are unwilling to postpone and one we intend to win. -JFK
For the last couple of months, I have been working with Kalman filter and its variations for aircraft tracking applications. I have found following resources helpful in the course of learning about Kalman filters.
Prof. Y. Bar-Shalom is well known in the area of tracking applications. This book by Bar-Shalom and co-authors is the standard text book for anyone interested in learning about applying Kalman filters. The authors aim to “make things simple, but not too simple; clear but not too clear“. The book not only presents theoretical derivation of filters, but also discusses implementation details. I have found the discussion on practical issues extremely helpful in the course of implementing the filters myself.
This is a book by Roger Labbe. This book covers a wide range of topics related to Kalman filters and its applications with focus on practical applications. What I liked about this book is that the entire book is composed as a Jupyter notebook. As a result, Roger not only presents the mathematical background but also presents code implementation of the filters. FilterPy is the accompanying python package which provides implementation of all the filters discussed in the book. If you are interested, it is straight forward to change the sample code in the chapter notebooks and see changes for yourself. This book is a fine example of literate programming.
I recently traveled Brisbane, Australia to attend the 41st ICASSP 2015 where I presented the poster on the unit circle MVDR beamformer. The accompanying paper should be available on IEEExplore soon. For now, I have made the pre-print available.
My submission for the upcoming ICASSP 2015 has accepted for presentation (Yay!). Following is the abstract of the accepted paper
The array polynomial is the z-transform of the array weights for a narrowband planewave beamformer using a uniform linear array (ULA). Evaluating the array polynomial on the unit circle in the complex plane yields the beampattern. The locations of the polynomial zeros on the unit circle indicate the nulls of the beampattern. For planewave signals measured with a ULA, the locations of the ensemble MVDR polynomial zeros are constrained on the unit circle. However, sample matrix inversion (SMI) MVDR polynomial zeros generally do not fall on the unit circle. The proposed unit circle MVDR (UC MVDR) projects the zeros of the SMI MVDR polynomial radially on the unit circle. This satisfies the constraint on the zeros of ensemble MVDR polynomial. Numerical simulations show that the UC MVDR beamformer suppresses interferers better than the SMI MVDR and the diagonal loaded MVDR beamformer and also improves the white noise gain (WNG).
What is the distribution of the phase of the product of two independent zero-mean complex-circular Gaussian random variables? I try to answer the question in this IPython notebook.
Data Science from Nepal
Its hard to miss “Data Science” or “Big Data” as the two hot topics at present. Wikipedia defines data science in the simplest terms as the science of extracting knowledge from data. The vast potential of data science applications is driving the job market and proportional investment from big companies. Consequently startups working in the area of data science ahave been mushrooming around the world.
Nepal hasn’t remaind untouched by the growing interest in data science. I have been following a string of startups from Nepal working in data science. These are exciting times for startup scenario in Nepal, and it is encouraging to see people experimenting with data science in their startup venture. Here I am listing some startups that I have been following:
- Oval Analytics – Your Data Science Partner
Oval Analytics is the brainchild of Hemanta Shrestha and Saurav Dhungana. Oval is perhaps the first technology company in Nepal with aim to provide data analytics services to local clients in addition to external clients. This is a challenging task given the limited market within the country. Oval Analytics wants to become an important part of the data science community in the country.
- Data Nepal – Nepal Unleashed
DataNepal was a startup with an aim to become the goto repository for “socio-economic, demographic, environmental, developmental and geospatial data “ related to Nepal. The data was mainly collected from public domain and made available in more friendly formats (JSON, CSV, XML).
- Graph Nepal
Graph Nepal is perhaps the first startup with focus on data visualization and infographics focused on local issues. Visualization is a powerful part of conveying the story based on big data analytics.
- Kathmandu Living Labs
- Cloud Factory
Let me know @sauravrt, about other startups from Nepal who are working in the area of data science, analytics and visualization. I’d be happy to know more of them and add to my list here.
Written with StackEdit.
I recently visited Washington DC, the country’s capital, with my wife and some friends. It was a three day visit over the Memorial day weekend. This was my second time in the capital. A combination of perfect weather and good company made this a memorable trip for us.
Travel: Our plan was to drive all the way to DC. On a normal traffic it should take us around 8 hrs to reach DC from Boston. We rented a car big enough to fit six people. We had three of us who could share the drive. Also we planned to use Waze app and Garmin GPS with live traffic to keep our eye on traffic condition ahead.
Lodging: We decided to try out Airbnb for our stay in DC. After couple of days of collaborative search we were able to find a host who would take in six guests. The host had good reviews from previous guests and place was located behind the US Naval Observatory . So we felt pretty confident about the host and neighborhood.
Day 0 ( May 23, 2014)
The reservation for the rented car had a pick up time of 12 pm, but a call to customer service early in the morning confirmed that we could pick up the car earlier. So three of us who would be driving set off towards the Logan airport where the rental car was located. After quick negotiation we were able to get a slightly bigger car (Chevy Suburban instead of Tahoe). On the hindsight we are glad we made that choice. The Suburban was plenty spacious of six people and had enough luggage space too.
We drove back to our apartment where we loaded our luggage onto the car and by 12 pm we were on the road. Our plan was to head out by 12 pm so that we would reach DC by 9 pm in the evening. So we were pretty pleased with our organization. We took I-90 W all the way to Sturbridge and split off to I-84 to head down south. We were worried that we would hit New York City evening rush hour traffic.
My work was presented at the recently concluded IEEE SSP2012 (Michigan). It was a poster titled Approximate Eigenvalue Distribution of a Cylindrically Isotropic Noise Sample Covariance Matrix. This work was done in collaboration with my adviser Prof. John R. Buck and Prof. Kathleen E. Wage from GMU.
Unfortunately, due to my internship commitments I wasn’t able to attend the actual conference. My adviser presented the poster on my behalf.