  With the development of intelligent transportation, growing attention has
been received to integrated sensing and communication (ISAC) systems. In this
paper, we formulate a novel passive sensing technique to obtain information on
the vehicle's direction of arrival (DOA) using reconfigurable intelligent
surfaces (RIS). A novel estimation method is proposed in the scenario with a
receiver using only one full-functional channel, where multiple measurements
for the DOA estimation are achieved by controlling the reflection matrix
(measurement matrix) in the RIS. Moreover, different from the existing
estimation methods, we also consider the interference signals introduced by
wireless communication in the ISAC system. Then, we propose a novel atomic
norm-based method to remove the interference signals and reconstruct the sparse
signal. Additionally, a novel Hankel-based multiple signal classification
(MUSIC) method is formulated to obtain the DOA information after the
interference removal. To reduce the interference signals more efficiently and
improve the performance of the sparse reconstruction, we optimize the
measurement matrix to improve the signal-to-interference-plus-noise ratio
(SINR). Finally, the theoretical Cram'{e}r-Rao lower bound (CRLB) is derived
for the ISAC system on the vehicle DOA estimation. Simulation results show that
the proposed method can achieve better performance in the DOA estimation, and
the corresponding CRLB with different distributions of the sensing nodes are
shown. The code for the proposed method is available online
https://github.com/chenpengseu/PassiveDOA-ISAC-RIS.git.
