Since the inception of coherent waveforms, it has been realized that the effect of non-uniform motion of a non-point like object can induce structure in the return spectrum of the waveform that can be exploited. The non-uniform Doppler spectrum has useful information that can be found in the spreading of the Doppler spectrum for the motion models: acceleration, jerk, quadric, and exponential slowdown as examples well as a characteristic of periodic motion. We illustrate this with examples relevant to automotive radar, tracking meteors with ambient sources, characterizing moving sources and other relevant examples.
An algorithm for solving the simultaneous hyperbolic equations that arise in multilateration using time difference of arrival measurements (TDOA) is presented. This weighted, non-iterative algorithm is able to reduce error by more than 50% over unweighted variations of the algorithm. This algorithm was developed for use in a passive multistatic sensor network. By using low gain antennas and TDOA, we are able to provide platforms with situational awareness while maintaining a low RCS.
We review various image processing algorithms for micro-UAV EO/IR sub-pixel jitter restoration. Since the micro-UAV, Silver Fox, cannot afford isolation coupling mounting from the turbulent aerodynamics of the airframe, we explore smart real-time software to mitigate the sub-pixel jitter effect. We define jitter to be sub-pixel or small-amplitude vibrations up to one pixel, as opposed to motion blur over several pixels for which there already exists real time correction algorithms used on other platforms. We divide the set of jitter correction algorithms into several categories: They are real time, pseudo-real time, or non-real-time, but they are all standalone, i.e. without relying on a library storage or flight data basis on-board the UAV. The top of the list is demonstrated and reported here using real-world data and a truly unsupervised, real-time algorithm.
The Fourier transform (FT) is often used to analyze transient and non-stationary signals even when such signals are not periodic in nature. We demonstrate how an adaptive wavelet transform (WT) can bring out signal details that the traditional FT cannot, as first shown by Szu et al. In 1992. The magnitude plot of the complex Morlet wavelet shows the evolution of the signal's energy in both time and frequency, while the phase plot pinpoints signal discontinuities at various scales. This information can be used to build a compact model and approximate representation of signals characterized by pulses. We are able to infer the physics of devices that generate EM pulses.
Digital halftoning is the process to render continuous-tone images on binary display devices such as printers. Although the transmission of halftone images to printers can be compressed using established lossless protocols, lossy compression methods of the original image can achieve higher efficiencies. We present some experimental work in developing a reversible wavelet-based image compression algorithm that is tuned for halftoning. We also describe a rendering algorithm which is based on the wavelet coefficients from the compressed domain, and which matches the number of dots to the average image intensity at multiple resolutions. Additionally, we address the issue of inverse halftoning using wavelet decompositions of the halftone data.