  Intelligent reflecting surface (IRS) has the potential to enhance sensing
performance, due to its capability of reshaping the echo signals. Different
from the existing literature, which has commonly focused on IRS beamforming
optimization, in this paper, we pay special attention to designing effective
signal processing approaches to extract sensing information from IRS-reshaped
echo signals. To this end, we investigate an IRS-assisted non-line-of-sight
(NLOS) target detection and multi-parameter estimation problem in orthogonal
frequency division multiplexing (OFDM) systems. To address this problem, we
first propose a novel detection and direction estimation framework, including a
low-overhead hierarchical codebook that allows the IRS to generate
three-dimensional beams with adjustable beam direction and width, a delay
spectrum peak-based beam training scheme for detection and direction
estimation, and a beam refinement scheme for further enhancing the accuracy of
the direction estimation. Then, we propose a target range and velocity
estimation scheme by extracting the delay-Doppler information from the
IRS-reshaped echo signals. Numerical results demonstrate that the proposed
schemes can achieve 99.7% target detection rate, a 10^{-3}-rad level direction
estimation accuracy, and a 10^{-6}-m/10^{-5}-m/s level range/velocity
estimation accuracy.
