Observations from the EarthCARE Cloud Profiling Radar (CPR) frequently contain spurious cloud signals caused by mirror images, multiple-scattering (MS) tails, and satellite mirror images (SMIs). These multiple-trip echoes are produced when transmitted radar pulses follow longer-than-nominal propagation paths and return within the reception window of subsequent pulses. Distinguishing and removing them is essential for scientific analyses using CPR observations. This study characterizes global properties of the multiple-trip echoes and evaluates the performance of the identification methods implemented in the JAXA Level 2A CPR one-sensor Echo product (CPR_ECO). For mirror images and MS tails, we adopt modelling approaches previously proposed for CloudSat-based analyses, whereas for SMIs we introduce a new method that exploits their characteristic altitude and Doppler-velocity signature associated with line-of-sight satellite-velocity contamination. Evaluations using collocated Atmospheric Lidar (ATLID) measurements, which provide CPR-independent cloud-top information, objectively show that the method properly identifies most of the multiple-trip echoes. Global statistical analyses using the identification flag reveal distinct geographical distributions, seasonal variations, vertical structures, and surface-state-dependent occurrence conditions among the three echo types. Mirror images are the most frequent type, and their distribution broadly follows cloud occurrence, with a preference for ice-free ocean. MS tails are concentrated in tropical and subtropical convective regions under strongly attenuating conditions. In contrast, SMIs occur almost exclusively over surfaces with near-saturated backscatter, such as melting sea ice and land with surface-water cover. These results provide a basis for improving multiple-trip echo identification and for addressing overlap cases in which spurious echoes contaminate genuine cloud signals.