1 research outputs found
Height estimation for automotive MIMO radar with group-sparse reconstruction
A method is developed for sequential azimuth and height estimation of small
objects at far distances in front of a moving vehicle using coherent or
mutually incoherent MIMO arrays. The model considers phases and amplitudes for
near-field multipath signals produced by specular non-diffusive
ground-reflections where the reflection phase shift and power attenuation due
to the interaction with the ground is assumed unknown. Group-sparsity allows
combining measurements along the trajectory of the vehicle provided that the
road is flat as well as measurements from multiple incoherent sensors at
different locations in the vehicle. It is shown in simulations that the
proposed approach significantly increases estimation accuracy and decreases
false alarms, both crucial for the detection of small objects at far distances.
This model is suitable for non-uniform sparse arrays and can be used for height
estimation using efficient methods such as block orthogonal matching pursuit.Comment: 1