# Passive Location for 5G OFDM Radiation Sources Based on Virtual Synthetic Aperture
## 1 Introduction  
Passive location technology has been constantly developing in the past decades [1]. Electronic reconnaissance is an important means to obtain battlefield electronic intelligence. Its main task is to monitor and intercept electromagnetic wave signals radiated by enemy military equipment (such as radar, radio communication, navigation and guidance, etc.) and obtain their technical parameters, communication content, location and other information. Thus, radiation source location by a single satellite plays an important role in electronic reconnaissance with the advantages of low power consumption, long detection distance, good concealment, and strong anti-interference ability [2]. With the development of 5G construction, the realization of satellite-Earth interconnection and the integration of communication, navigation and remote sensing is the current development hotspot. In addition, satellite communication is being vigorously developed to realize global communication without the limit of altitude and region. Therefore, realizing 5G radiation source location can not only shield, interfere and attack enemy ground base stations and satellite communication users, but can also realize the accurate location of its own satellite communication users to provide better user services, which has important military, civil and commercial value. The methods of passive location by single satellite commonly use location parameters of direction of arrival (DOA) or change rate of Doppler frequency. DOA is usuallymeasured by phase interferometer or antenna array. For phase interferometer systems, the problem is that a long baseline can obtain highly accurate location information but causes phase ambiguity, which needs complex antenna structures to solve [3; 4]. For antenna array systems, a long array can reach high accuracy but is limited in a moving platform [5]. Antenna array DOA estimation algorithms include conventional beamformer (CBF), multiple signal classification (MUSIC), and maximum likelihood estimator (MLE) [6]. With the development of neural networks, the DOA estimation method based on deep learning has been widely applied, which can reduce computational complexity [7]. DOA estimation with a traditional scalar sensor requires complex antenna structures, so an electromagnetic vector sensor (EMVS) array is used instead of a scalar sensor array for two-dimensional DOA estimation, which has high estimation accuracy. In addition, DOA estimation with an EMVS array is insensitive to sensor position, which makes EMVS more flexible than traditional scalar sensor arrays [8; 9]. The Doppler location systems measure the Doppler change rates of the same radiation source by the satellite at different locations and obtain the radiation source location by combining the position information of the satellite platform at each moment [10; 11; 12; 13]. Compared with the DOA method, the Doppler system has a simpler structure but needs a long time to measure the Doppler information from many positions, and the location accuracy is affected by the Doppler measurement accuracy. Long-time sampling data are needed to measure the instantaneous Doppler information, but causes the change of Doppler. Multi-satellite passive location systems have high location accuracy. Their most widely used location methods are time difference of arrival (TDOA), frequency difference of arrival (FDOA), and the joint location method, which has high location accuracy [14; 15; 16]. Other location information can also be combined to obtain high-accuracy source location, such as combining TDOA, FDOA and differential Doppler rate (DDR) [17], or time of arrival (TOA) and TDOA [18], etc. However, issues such as time synchronization need to be considered, which result in high system complexity and cost. In contrast, although single-satellite passive location systems are not accurate enough, they are widely used because of their low cost and simple system setup.