Computational Aspects of Maximum Likelihood DOA Estimation of Two Targets with Applications to Automotive Radar
Direction-of-arrival (DOA) estimation of two targets with a single snapshot plays an important role in many practically relevant scenarios in automotive radar for driver assistance systems. Conventional Fourier-based methods cannot resolve closely spaced
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Computational Aspects of Maximum Likelihood DOA Estimation of Two Targets with Applications to Automotive Radar Philipp Heidenreich and Abdelhak M. Zoubir
Abstract Direction-of-arrival (DOA) estimation of two targets with a single snapshot plays an important role in many practically relevant scenarios in automotive radar for driver assistance systems. Conventional Fourier-based methods cannot resolve closely spaced targets, and high-resolution methods are required. Thus, we consider the maximum likelihood DOA estimator, which is applicable with a single snapshot. To reduce the computational burden, we propose a grid search procedure with a simplified objective function. The required projection operators are pre-calculated off-line and stored. To save storage space, we further propose a rotational shift of the field of view such that the relevant angular sector, which has to be evaluated, is centered with respect to the broadside. The final estimates are obtained using a quadratic interpolation. An example is presented to demonstrate the proposed method. Also, results obtained with experimental data from a typical application in automotive radar are shown. Keywords Automotive radar • Direction of arrival (DOA) • Driver assistance systems • Maximum likelihood (ML) estimation
P. Heidenreich (*) ADC Automotive Distance Control Systems GmbH, Peter-Dornier-Str. 10, 88131 Lindau, Germany e-mail: [email protected] A.M. Zoubir Signal Processing Group, Technische Universita¨t Darmstadt, Merckstr. 25, 64283 Darmstadt, Germany e-mail: [email protected] G. Schmidt et al. (eds.), Smart Mobile In-Vehicle Systems: Next Generation Advancements, DOI 10.1007/978-1-4614-9120-0_1, © Springer Science+Business Media New York 2014
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P. Heidenreich and A.M. Zoubir
Introduction
Ever-increasing amount of advanced signal processing algorithms is used in various automotive applications [1, 2], e.g., advanced driver assistance systems [3]. These utilize from various sensors to determine the environment of a vehicle. From an identified traffic situation, the driver assistance system regulates the behavior of the vehicle, instructs the driver, or warns the driver in dangerous situations. Often radar sensors are employed, which work reliably even in bad weather conditions, and can provide accurate measurements of the range and relative velocity of multiple targets. To also measure the lateral position of a target, an array of antennas in horizontal direction with digital beamforming can be applied. For typical applications such as collision avoidance or adaptive cruise control (ACC), it is essential to accurately estimate the lateral position and to be able to resolve multiple closely spaced targets. For the array system with limited aperture, this can be achieved with high-resolution processing, which is considered computationally intensive and numerically complex, so that real-time implementation becomes a challenging task. A pulsed radar system with an array of receive antennas can be effect
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