## 1 Introduction  
The extraction of vegetation characteristics from radar data has emerged as a significant concern in remote sensing [1, 2, 3, 4]. The demand for ecosystem monitoring, natural resource management, including forests, and environmental change assessment is rising. A substantial number of experiments are necessary to acquire important data. Diverse models are employed to achieve correlation, phase, and coherence attributes [5, 6, 7, 8, 9, 10, 11, 12, 13]. Refs. [12, 13] employ models to ascertain correlation features. It is claimed that certain models yield consistent outcomes. Additionally, other parameters are thought to influence the features and sensitivity analysis. Radar functions as a distance measurement instrument, exemplified by altimeters, or for imaging purposes, as seen in Side-Looking Airborne Radar (SLAR) and Synthetic Aperture Radar (SAR). SAR is a radar system that generates a highly focused effective beam through the sophisticated processing of radar data [5, 6, 7, 8]. SAR signal processing involves coherent phase correction that rectifies the particular phase shift history of the signal reflected from a designated location on the ground, accounting for the velocity of the aircraft (radar). The necessary phase adjustment can be inferred from the anticipated phase history of a ground return to an aerial radar [14; 15; 16]. Interferometric synthetic aperture radar (InSAR) technology is employed in remote sensing and geodesy. This geodetic technique employs variations in wave phases returning to the satellite or aircraft to generate digital elevations or surface alterations from two or more synthetic aperture radar images. Numerous studies and applications exist for InSAR and other radar technologies [16; 17; 18; 19; 20; 21; 22; 23; 24; 25; 26]. These studies delineate the derivation of signal statistics, an efficient estimator for the interferometric phase, and the requisite equations for calculating the height error budget. Additionally, they provide a set of design guidelines for enhancing InSAR performance. It was determined that interferometric mapping offers a high-resolution topographic system capable of functioning effectively in challenging topographical conditions. It develops a model that incorporates both radar system characteristics and scene scattering parameters, utilizing it to analyze observations in a forested region with varying coherence. The interferometric height discontinuity exhibits a strong correlation with a dense forest. The literature review indicates that initial studies have employed mathematics to clarify InSAR observations through the physical characteristics of vegetation, such as scatterer amplitude, extinction coefficient, incident angle, baseline distance, and the height of the ground surface or the depth of the vegetation layer [8; 12; 13; 17; 18; 19; 20; 21; 23]. The comparable frequency decorrelation bandwidth is the only thing that matters when trying to figure out the height of a spread target. The baseline distance has no effect on this. There are references [8; 19; 20] that describe how to evaluate the extinction, physical height, and height of the scattering phase center in a closed, uniform, semi-infinite canopy using InSAR data. The methods for extracting vegetation characteristics and the underlying ground surface topography from InSAR data are proposed in both [PERSON]'s and [PERSON]'s Model [12; 13; 17]. The modeling procedure encompasses the simulation of electromagnetic scattering and radar processing that constitute the InSAR observations. The vegetation and topography parameters are then selected for estimation. Parameter discrepancies are then assessed against the performance of InSAR sensors, and parameter estimates resulting from InSAR data are presented and compared to real-world observations.