Interferometric Synthetic Aperture Radar (InSAR) technology provides a useful tool for quantitatively measuring the deformation of the earth, influenced by natural factors (earthquake, subsidence, and landslide) and human factors (construction of structures, drilling, and the overexploitation of underground water aquifers). In this context, time-series analysis of radar images allows the monitoring of long-term deformations and analysis of geodynamic phenomena. However, the radar interferometric technique is only capable of measuring the displacement along the satellite's line of sight (LOS), and one interferometric LOS observation is not capable of extracting a 3D displacement field. Thus, this will limit the potential of the InSAR technique to the study of many tectonic phenomena that require a comprehensive understanding of their three-dimensional displacement components. The purpose of this paper is to provide a comprehensive overview of the main methods of retrieval of the earth's 3D surface field using radar interferometric observations, including; recent advances in this field and the advantages and weaknesses of each of these methods. In fact, in this paper, the existing methods for recovering 3D surface displacement fields using radar interferometry measurements developed in recent decades are reviewed in detail. Several methods are used to exploit the potential of InSAR for 3D surface displacement determination. In general, these methods can be divided into three general categories. The first is the use of homogeneous data, including radar images of other satellites or the use of independent radar imaging geometries. In this category, we can mention ideas such as 1) Using the observation combination along the satellite LOS in at least three independent geometries (DInSAR) 2) Combining the observations along the LOS with the azimuth observations (azimuth offset, MAI) and 3) Overlapping between the burst (burst overlap interferometry) in the Sentinel satellite data. In the first batch methods, the accuracy of estimating 3D field components for different geometries is estimated. However, it has been observed that the least accuracy will be related to the north-south component retrieval. The second batch method is the use of heterogeneous data (independent geodetic observations such as GPS, leveling, gravity data, etc.), which through combining GPS displacement vectors or leveling with observations from radar interferometry (the so-called data fusion) tries to recover the real 3D dimensional field, And finally, the third set of methods includes previous studies and experiences of how to relocate the area or use assumptions about the relocation of the area, in which there are two methods; 1) Ignoring one or two displacement component (if the displacement mechanism is known), which provides an analytical form for measuring the error in retrieving the other components and evaluates with similar data. 2) Considering the hypothetical models for reshaping or combining geophysical models with radar interferometry data. Each of the methods mentioned above is used for retrieving the 3D displacement field and have their strengths and weaknesses, Which are discussed in detail in this article. Finally, we hope to provide useful guidance for choosing a suitable method to resolve the challenging issues of extracting a 3D surface displacement field.