###### Abstract
Using this method, a system can calculate the required frequency adjustment value and use it to pre-compensate uplink transmissions and to maintain multi-access orthogonality at the receiver. Unfortunately, the range of the errors in the estimated Doppler shifts is between \(-1.5\) kHz and \(1.5\) kHz, which is not acceptable in many radar applications. Moreover, it is not adequate for radar systems that use a single carrier frequency. In [15], a Doppler cancellation module that integrates data from multiple signals to eliminate Doppler effects from Doppler-intolerant signals, such as phase-modulated signals, is introduced. This allows the use of high-resolution waveforms to detect high-speed targets, even if they are Doppler-intolerant. However, this method does not provide Doppler value estimation and dictates that one of the integrated signals is used for Doppler estimation. In [16], the authors presented an enhanced orthogonal matching pursuit (OMP) algorithm to directly estimate the velocity and the acceleration of the target. They rely on pre-constructing a dictionary for sparse motion parameters of the target. This renders the Doppler frequency migration unnecessary. While effective for estimating the velocity and the acceleration, this method is iterative, relies on the greedy nature of OMP, and can be very expensive, especially for large dictionaries of the parameter space. The authors of [17] presented another method for recovering radar waveforms and estimating Doppler values for high-speed targets using two types of waveforms: phase-modulated and unmodulated waveforms. This technique is primarily effective for high-speed targets. For low-speed targets, the authors recommend using traditional Doppler estimation methods, thereby incorporating the proposed method as a sub-module within a typical radar system. Doppler values are estimated using the FFT of the unmodulated signal. Consequently, the Doppler ambiguity is constrained by the repetition time and the resolution of FFT. It is worth highlighting that, to estimate the Doppler frequency, most of the methods mentioned above rely on DFT, which makes them unable to resolve the exact Doppler frequency due to DFT's inherent Doppler ambiguity. Moreover, many of the available techniques for estimating Doppler frequency are not suitable for bi-phase signals. In this paper, we present an efficient and inexpensive algorithm that accurately estimates the Doppler value by relying on just one pulse. The algorithm enhances the robustness of its estimate by using an ensemble averaging of Doppler estimators based on the next few successive pulses. To increase the accuracy even further, we rely on an iterative technique to progressively remove any Doppler residue. Since the estimation is performed in the time domain, the proposed algorithm is immune to all Doppler ambiguities. Thereby, the Doppler ambiguity that occurs in the conventional Doppler calculations does not affect our algorithm. Furthermore, the proposed algorithm segregates the Doppler effect from the signal, removes the Doppler effect from any bi-phased waveform using a sequence of subsystems, and enables the return of the waveform to its well-known shape at low signal-to-noise-ratios (SNRs) to produce a reliable range resolution. By doing so, we decrease the time and hardware complexities from which the conventional radar systems suffer, as they rely on expensive MTD processors with a large coherent pulse interval (CPI). In addition, we circumvent the main bottleneck problem in using bi-phase codes for moving target detection, especially for high-speed targets. Figure 1 shows a block diagram of our proposed modules in a conventional radar system. Figure 1: A brief block diagram of our proposed radar system. As the block diagram depicts, the proposed module can be viewed as an add-on component that sits between the ADC and the rest of the conventional radar receiver modules.