# Radar Emitter Structure Inversion Method Based on Metric and Deep Learning
## 2 Problem Definition  
A radar emitter is the core component of a radar system. Radar emitters are typically classified as pulse-modulated emitters and continuous wave emitters. Pulse-modulated emitters are usually categorized into single-stage oscillating emitters and main vibration amplification emitters. Most radars, particularly those that are highly stable and those with high-performance tracking, telemetry, and control (TT&C), as well as phased array radars, have adopted a main vibration amplification radar emitter. Recently, with the rapid development of gallium arsenide (GaAs) and gallium nitride (GaN), studies on all-solid-state radar emitters in the C-band and X-band have approached the practical stage. All all-solid-state radar emitters are generally classified into two categories: a high-power solid-state emitter with a centralized synthesis output structure and a distributed synthetic phased radar emitter. Therefore, there is a variety of RES due to these different structure design parameters. Generally, the radar emitter source is mainly composed of a signal source and an RF link module [43; 44]. The signal source generates a source signal of the desired frequency. The RF mixer and RF amplifier are the core modules of the RF link. The RF mixer is responsible for moving the intermediate frequency signal spectrum to the RF area, and the RF amplifier is responsible for amplifying the input RF signal. Due to the defects of the underlying physical components, the signal source has phase truncation errors, which makes RF signals appear as \"burrs\" (spurious information). RF modules, such as RF mixers and RF amplifiers, have nonlinear distortion and phase noise, which will produce high harmonics and intermodulation distortion. The phase noise level of the RF mixer can introduce significant differences to the RF signal in both time and time-frequency domains. The different third-order intercept points (IP3) of the RF amplifier will cause different amplitudes in the RF signal. Because different classes of RES are composed of different structure design parameters, such as RES1 having only one stage of amplification while RES2 is designed for two-stage amplification, there are structure differences between different classes of RES. At the same time, under the same class of RES, different individuals have the same structure design parameters and use the same components, but because there are subtle differences between each component; this subtle difference is called \"RF individual information\" in this paper, and it is also called an \"RF fingerprint\" [45]. This results in individual differences among different individuals under the same RES. Therefore, there are essential differences between REI identification and RES inversion in this paper. As shown in Figure 2, red, yellow, and green represent three classes of RES, and numbers 1, 2, and 3 correspond to three different operating parameters, while the number 4 corresponds to unknown operating parameters. The RF structure information carried by RF signals and transmitted by radar emitters with different structures is noticeably different under ideal conditions. All types of neural networks can be used for classification and recognition if using the homo-mode operating parameter--that is, 1, 2, and 3 are the same operating parameters--and the training data and corresponding labels are good. Figure 2: Influence of changes in the operating parameters of RES inversion. (**a**) Influence of hetero-mode operating parameters. (**b**) Influence of unknown operating parameter. With the emergence of multi-functional and phased array radars, operating parameters in relation to different tasks can be changed. For instance, multi-functional radars support various modes, such as tracking and searching, single-target tracking, multi-target tracking, and others. The performance of the neural network will be seriously affected either by RES inversion or by REI identification under hetero-mode operating parameters.