The evolution of single-chip high-frequency circuits helped manufacture radars with better accuracy, lower costs, and smaller footprints. This paper describes a compact 24 GHz frequency-modulated-continuous-wave radar that can be used to aid the visually impaired during their outdoor journeys. The project helps partially or totally blind people avoid collision with their environment without the use of a white cane. Details about the implemented signal processing algorithms are also given. Although its main purpose is to assist the visually impaired, the device can perform diverse tasks such as rangedirection mapping, velocity estimation, presence detection, and vital sign monitoring. The experimental result section demonstrates the device's capabilities through different use-cases.
In multiple-input multiple-output radar, to localize a target and estimate its reflection coefficient, a given cost function is usually optimized over a grid of points. The performance of such algorithms is directly affected by the grid resolution. Increasing the number of grid points enhances the resolution of the estimator but also increases its computational complexity exponentially. In this work, two reduced complexity algorithms are derived based on Capon and amplitude and phase estimation (APES) to estimate the reflection coefficient, angular location and, Doppler shift of multiple moving targets. By exploiting the structure of the terms, the cost-function is brought into a form that allows us to apply the two-dimensional fast-Fouriertransform (2D-FFT) and reduce the computational complexity of estimation. Using low resolution 2D-FFT, the proposed algorithm identifies sub-optimal estimates and feeds them as initial points to the derived Newton gradient algorithm. In contrast to the gridbased search algorithms, the proposed algorithm can optimally estimate on-and off-the-grid targets in very low computational complexity. A new APES cost-function with better estimation performance is also discussed. Generalized expressions of the Cramér-Rao lower bound are derived to asses the performance of the proposed algorithm.
This application claims priority to, and the benefit of, co-pending U.S. provisional application entitled "Generation of Correlated Finite Alphabet Waveforms Using Gaussian Random Variables" having serial no. 62/022,832, filed July 10, 2014, and co-pending U.S. provisional application entitled "Generation of Correlated Finite Alphabet Waveforms Using Gaussian Random Variables" having serial no. 14/751,916, filed June 26, 2015, both of which are hereby incorporated by reference in their entirety. BACKGROUND [0002] Correlated waveforms or random variables (RVs) are utilized in a number of fields. For example, in communications the noise at different receive antennas can be correlated (colored). Similarly depending on the radar parameters and sea surface conditions, each component of the received sea clutter may be correlated. In both of these applications, correlated RVs are generated for simulations. Therefore, generation of such waveforms is not challenging. Software radar is an emerging technology, where characteristics of radar, such as beampattern, signal to interference plus noise ratio (SINR), and side-lobe-levels (SLLs), can be changed through software without changing any hardware. This technology requires the design of correlated waveforms. To use such waveforms in practice, their peak-to-average power ratio (PAPR) should be close to unity and the symbols of the waveform should be drawn from finite alphabets. Generation of such waveforms is very challenging.
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