## 1 Introduction  
The wideband linear frequency modulation (LFM) signal is widely used in modern wideband radar systems. Compared with the narrow-band LFM signal, it can achieve much better quality in inverse synthetic aperture radar (ISAR) imaging, due to the higher range resolution [1; 2; 3; 4]. However, the motions of the target often cause range migration (RM) and Doppler frequency migration (DFM) effects in the received signals, which will degrade the imaging quality. Therefore, the object's motion parameters should be estimated and compensated before imaging [5; 6; 7; 8]. Besides, the accuracy of motion parameters estimation also affects the performance of target tracking and identification. Thus, high precision motion parameters estimation is necessary and attracts much more attention in modern wideband radar systems [1; 2; 3; 4; 5; 6; 7; 8; 9]. For wideband radars, the estimation methods of motion parameters can be divided into two types: parameter-searching methods and non-parameter-searching methods. A parameter-searchingmethod maximizes or minimizes some criterion by searching the motion parameters step by step. Many of the traditional range alignment methods [4; 8; 10; 11; 12; 13; 14; 15; 16] in inverse synthetic aperture radar (ISAR) imaging are parameter-searching methods, such as spatial domain realignment [8], adaptive joint time-frequency technique [10] and minimum entropy method [15; 16]. Spatial domain realignment [8] defines a correlation function between two envelops of echo signals with delays. The amount of envelope shift is determined by searching the delay to obtain the maximum of the correlation function. In [10], the radar echo signal is projected to a set of basis functions, which are constructed with different parameters. A searching procedure is conducted to maximize the projection value, and then, the motion parameters are estimated. The minimum entropy method introduces a 1D entropy function to determine the degree of alignment between radar echoes [15; 16]. As the delay, which minimizes the entropy, is searched with the step determined by the bandwidth of the transmitted signal, the accuracy of the estimated parameters is limited by the delay step. To perform high precision motion parameters estimation, the Radon-Fourier transform (RFT) method is proposed for multi-pulse energy accumulation [9; 17; 18]. The RFT method is a multidimensional searching method and achieves a good performance of motion parameters estimation because of long coherent integration time. A common drawback of these parameter-searching methods is that their computation is highly complex, when they are applied in the wideband radar systems. In the non-parameter-searching methods, the keystone transform (KT) is able to eliminate the RM effect based on long time coherent integration technology [19; 20; 21]. However, the DFM induced by acceleration cannot be removed by KT. In [22], a non-searching ISAR range alignment method based on minimizing the entropy of the average range profile (ARP) is proposed. An iterative procedure is utilized to estimate the delays of envelops, of which the precision is determined by the range resolution. Meanwhile, an interpolation is employed on the envelops to improve the estimation precision. However, the iterative procedure and the interpolation operation significantly increase the computational complexity. Moreover, the phase information is not used for estimation in [22]. In [23], a novel estimation algorithm of motion parameters is proposed for ISAR imaging, based on KT and the adjacent cross-correlation function (ACCF). Then, a fast non-parameter-searching method based on ACCF is proposed for target motion estimation, target detection and ISAR imaging [24; 25; 26; 27; 28]. There are two differences between the two methods in [23] and in [24; 25; 26; 27; 28]. The first one is that the KT is not utilized in [24; 25; 26; 27; 28], and the other one is that the choice of the scaling factors is improved in [28]; thus, better performance is obtained under low SNR conditions.