Systems and methods for resolving elevation ambiguity include acquiring, using a 1-D horizontal radar antenna array, a radar frame with range and azimuth information, and predicting a target elevation based on the frame by computing a depth map with a plurality of target depths assigned to corresponding azimuth-elevation pairs. Computing the depth map includes processing the radar frame with an encoder-decoder structured deep convolutional neural network (CNN). The CNN may be trained with a dataset including training radar frames acquired in a number of environments, and compensated ground truth depth maps associated with those environments. The compensated ground truth depth maps may be generated by subtracting a ground-depth from a corresponding ground truth depth map. The ground truth depth maps may be acquired with a 2-D range sensor, such as a LiDAR sensor, a 2-D radar sensor, and/or an IR sensor. The radar frame may also include Doppler data.