## 1 Introduction  
The radar electronic countermeasure (ECM) interferes with the normal operation of radar by confusing the physical targets (PTs) with the false targets (FTs) and/or drowning PTs in the interference signal, which seriously hinders the detection and tracking of the target [1]. With the application and development of digital radio frequency memory (DRFM), active deception jamming has become an efficient and widely used means of ECM. The repeater jammer performs the time delay, doppler and radar cross section (RCS) modulation on the intercepted radar signal to generate various false targets that resemble the physical target in multiple dimensions, such as range deception FT, velocity deception FT and range velocity joint deception FT [2, 3]. The electronic counter-countermeasures (ECCMs) for active deception jamming have been developing from the early monostatic radar system to the distributed multistatic radar system [4, 5]. Compared with the monostatic radar with limited resources, the multistatic radar system can perceive the environment from multiple dimensions and perspectives and benefits from fusion processing, therefore improving the performance on target detection [6, 7], target tracking [8, 9] and ECCM [10, 11]. The multistatic radar system can suppress jamming signals or discriminate false targets by fusing and processing the redundant detection information of different receivers. According to the difference in fusion processing, the ECCM for active deception jamming can be categorized into data-level fusion methods and signal-level fusion methods [12]. For data-level fusion methods, the target measurement information in each receiver is sent to the fusion center for fusion processing, which includes the primary and filtered information, such as radial distance, angle, radial velocity and the track information. The data-level fusion is mainly based on the spatial correlation difference between physical and active false targets [13]. For the physical target, its motion states (location and velocity vector) converted by each local measurement information are approximately the same in the unified coordinate system. Due to the silent operation of the receiver station in the multistatic radar system, it is difficult for the jammer to generate the cooperative active deception target for the whole multistatic radar system. As a result, the converted motion states are generally scattered in the unified coordinate system. At first, only the spatial correlation of location is made use of to discriminate false targets. According to the difference in location correlation between physical and false targets, a common origin test method, namely the location information association (LIA) method, is proposed based on Mahalanobis distance to discriminate false targets in a T/R-R bistatic radar architecture in [14]. Aiming at multiple false targets, the nearest neighbor association is firstly performed to avoid the target combination explosion, and then a dot association algorithm is designed with an adaptive threshold for homologous detection in [15]. Besides the nearest neighbor association with location, a discrimination process is presented based on nearest neighbor angle information to reduce the computational complexity and improve the target discrimination probability in [16]. Then, the spatial correlation of the velocity vector is utilized to discriminate false targets. For velocity deception false targets, the Doppler frequency of the same false target in each receiver station is similar when the jammer is stationary or moves slowly; meanwhile, that of the same physical target usually varies with receivers, which is exploited to discriminate false targets in [17]. Combining the spatial correlation of location and velocity vector, a discrimination method is proposed within the Doppler domain and range domain to counter range-velocity joint deception jamming in [18]. However, the velocity effect of the jammer is not dealt with on the discrimination performance of the methods [17; 18].