Tag: Complex Sinusoids

Maximum velocity in an FMCW radar
DSP / Localization

FMCW Radar Part 3 – Design Guidelines

The Bloom’s Taxonomy describes the levels of mastery one attains in a field. Its last two stages are Synthesis and Evaluation. This is where the masters can be differentiated from the experts. In a job interview, for example, a good technique to judge a candidate’s ability is to ask them where the system in question breaks. A little learning is a dangerous thing Drink deep, or taste not the Pierian spring There shallow draughts intoxicate the brain And drinking largely sobers us again While the first two parts of the FMCW radar series addressed the lower levels, Part 3 is

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Orange vs tangerine
DSP

The Fourier Doppelgangers

It is well known that Fourier Transform is unique under certain conditions that are satisfied by almost all practical signals. Then, how can we resolve the following contradiction? Consider a sinc pulse and Linear Frequency Modulated (LFM) pulse (a chirp) in time domain. The sinc pulse is defined as \[ \text{sinc}(t) = \frac{sin(\pi t)}{\pi t} \] Now the spectrum of a sinc pulse in time in an ideal case is a rectangular signal in frequency domain, which is the most fundamental relation in signal processing. Both the sinc pulse and its spectrum are plotted in the left half of the

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A quarter sample rate complex sinusoid
DSP

Spectral Shift without any Multiplications

One of the great advantages of Digital Signal Processing (DSP) is an unexpected simplification of operations in seemingly complicated scenarios. See the Cascade Integrator Comb (CIC) filters for how to accomplish the task of sample rate conversion along with filtering with minimal resources. As another example, in wireless communications and many other applications, a frequency translation is often required in which the spectrum of a signal centered at a particular frequency needs to be moved to another frequency. From the properties of Fourier Transform, a shift by frequency $\omega_0=2\pi F_0$ requires sample-by-sample multiplication with a complex sinusoid $e^{j\omega_0 t}$. \[

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Discrete Fourier Transform (DFT) of a DFT-even sequence
DSP

The Beauty of Symmetry in Fourier Transform

In 1978, Fred Harris was a relatively unknown faculty member at the San Diego State University when he published his landmark paper titled On the use of windows for harmonic analysis with the discrete Fourier transform. That paper made him a superstar in DSP community. It presented a brief overview of signal windows and their impact on the detection of harmonic signals in the presence of broad-band noise and nearby harmonic interference. More importantly, he pointed out several common errors in the application of windows when used in the context of Discrete Fourier Transform (DFT). Today I am going to

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Interaction between populations of rabbits and foxes
DSP

Rabbits, Foxes and IQ Signals

If we pay attention, each term in a mathematical equation carries a meaning that resonates with common sense. Today I will explain where Lotka-Volterra equations come from. These equations describe the dynamics of a biological interaction in which a predator (e.g., foxes) and a prey species (e.g., rabbits) engage with each other in a continuous struggle for survival. We will see that the math expressions just line up to describe the phenomenon almost as in words. Moreover, they have a little connection to IQ signals, the fundamental concept in digital signal processing, that will also be presented in the article.

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