Displaced Sensor Automotive Radar Imaging

Understand

Displaced automotive sensor imaging exploits joint processing of the data acquired from multiple radar units, each of which may have limited individual resources, to enhance the localization accuracy.

• Prior works either consider perfect synchronization among the sensors, employ single antenna radars, entail high processing cost, or lack performance analyses.
• Contrary to these works, we develop a displaced multiple-input multiple-output (MIMO) frequency-modulated continuous-wave (FMCW) radar signal model under coarse synchronization with only frame-level alignment.
• We derive Bayesian performance bounds for the common automotive radar processing modes such as point-cloud-based fusion as well as raw-signal-based non-coherent and coherent imaging.