k- and Doppler Velocity Decomposition-Based Range Points’ Migration for 3-D Localization With Millimeter Wave Radar

A <inline-formula> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula>-space and Doppler velocity decomposition based on an accurate millimeter wave (mmW) 3-D target localization method is presented, using the range points’ migration (RPM) method to provide multi-information associated with point clouds. The incoherent method, known as RPM, has a number of advantages over coherent localization, including avoiding a false response due to phase uncertainty or the necessity for highly accurate phase calibration in multiple arrays. However, various concerns must be addressed to retain the benefit of high-frequency mmW radar. In order to bring some benefits of high-frequency mmW radar into RPM scheme, this study introduces the <inline-formula> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula>-space and Doppler velocity decomposition schemes for multiple objects moving at different speeds into the RPM scheme, where a new weighted term is introduced. In addition, the RPM point cloud is incorporated with the incoherent Doppler velocity estimation method known as the weighted kernel density (WKD) method, which provides a multifunctional 3-D localization. The mmW radar experiment in the 79-GHz band demonstrates that our proposed method achieves accurate 3-D Doppler-associated localization, even with a small aperture array.