Orthogonal time-frequency space (OTFS) is a new modulation technology that can adapt to the time-frequency double dispersion propagation characteristics of channels in a high-speed mobile environment; it has attracted extensive attention in industry [10; 11; 12]. A time-varying channel in the time-frequency (TF) domain is changed into a time-invariant channel in the DD domain using OTFS modulation. After such a two-dimensional transformation, the transmitted data symbols are subjected to minor subcarrier interference, and all symbols in the same OTFS data frame experience slow fading independent of time selectivity. OTFS modulation is carried out in the DD domain. At present, OTFS modulation has made certain research progress in many aspects, such as system performance analysis and modulation and demodulation algorithms. It is assumed in [10] that the ideal pulse-forming waveform satisfies orthogonal criteria in both time and frequency, but in reality, this is not possible because of [PERSON]'s uncertainty principle. As a result, the biorthogonality assumption was loosened, and an OFDM-based OTFS modulation system was presented in [13; 14]. This system takes into account the cyclic prefix (CP) of each OFDM symbol in the OTFS frame as well as the non-ideal rectangular pulse-shaping waveform. This benefit stems from the simplicity of implementation, but it also introduces the issue of high out-of-band radiation causing interference with adjacent channels. At the moment, frequency local pulse shaping [15] and time-domain windowing technology [16] are the two major techniques for maximizing out-of-band attenuation by lowering out-of-band radiation. Compared with the TF domain, the advantage of the DD domain is that only a small area, which is based on the channel response that will be introduced in the second part of the system model, is needed to describe the channel, and it has stronger sparsity for better channel estimation. Currently, the main technical research on OTFS modulation involves the estimation of channel state information and data detection after estimation. [PERSON]. [17] proposed an embedded pilot-assisted channel estimation scheme. The delay-Doppler plane's arrangement rules for data symbols, pilot symbols, and guard symbols were created to successfully prevent pilot symbols and data symbols from interfering with one another during each OTFS frame. The pilots were created for multipath channels with integer and fractional Doppler shifts using the OTFS modulation technology. However, if only one pilot symbol was inserted, it caused high peak-to-average-power ratio (PAPR) problems. For example, in this article, pilot power is greater than data power. In [18], a channel estimation and data detection framework based on a superposition pilot was proposed. This framework superimposes a low-power pilot on data symbols in the DD domain, thus increasing the space of data transmission and effectively improving the spectral efficiency of OTFS modulation transmission. Such a design induces high computation complexity, and the interference between data and pilot symbol also reduces the estimated accuracy. As emphasized in [19], integer approximation cannot adequately simulate the channel's noninteger delay and Doppler shift. Therefore, using an orthogonal matching pursuit approach based on binary refinement estimation, which has a tolerable computing complexity and much lower estimated normalized mean square error, has been suggested. According to the sparseness of the channel in the delay-Doppler domain, ref. [20] suggested a new pilot mode and a channel estimate method based on sparse Bayesian learning (SBL). In this new pilot pattern, the guard interval was not set, and the data and pilot had the same energy. To update the parameters in the previous model using the expectation maximum (EM) algorithm, a sparse Bayesian learning framework was provided. Channel estimation was treated as a sparse recovery problem.