Hybrid decision and data adaptive antenna array processing for collision avoidance radar
In this paper we describe a hybrid data and decision adaptive beam forming and processing strategy using a novel W-band (75-84 GHz) phased array architecture for automotive collision avoidance radars. We use the term `decision adaptive' to denote the situation where the output of a tracking algorithm initializes the weight vector of the antenna array such that the main formed beam can be coarsely steered toward a desired, conjectured target location and clutter can be nulled. We use `data adaptive' in the classic sense where the structure of the data provides fine angular resolution target angle estimates. This is also known as digital beamforming (DBF). This type of approach has three advantages for an automotive radar system: 1) the coarse direction beam weights are stored a priori and a simple look up table is used which makes real time computation trivial; 2) the DBF algorithm is applied at a lower dimension which alleviates both training and computation burdens; and 3) a simplified antenna array system can be used in which the various antenna channels are weighted and pre-combined into subarrays prior to the receiver electronics. This reduces on-chip real estate burden in manufacturing. We will show via analysis and simulation the performance of such a system.
2014 International Conference on Connected Vehicles and Expo (ICCVE)
Lee, J. S.,
Hybrid decision and data adaptive antenna array processing for collision avoidance radar.
2014 International Conference on Connected Vehicles and Expo (ICCVE),
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