# Sep-RefineNet: A Deinterleaving Method for Radar Signals Based on Semantic Segmentation
## 2 Related Work  
The purpose of radar signals deinterleaving is to separate the received pulse stream according to each radar emitter, which is shown in Figure 1.  
Deinterleaving generally uses the following PDW, such as TOA, direction of arrival, pulse width, radio frequency, and pulse amplitude. Normally, signal deinterleaving is divided into two steps. One is to dilute the pulse stream density through pre-sorting, and the other is to complete the main sorting through TOA sequence [12]. The parameter for the main sorting is PRI, which is the difference between the TOA of two adjacent pulses of the same radar emitter. Its mathematical model is \(PRI=TOA_{i+1}-TOA_{i}\). Radar with different working modes and systems may have different PRI modulation modes, such as constant PRI, jittered PRI, and staggered PRI. The constant PRI is considered to be fixed in two adjacent pulses of the radar emitter under ideal conditions. In practice, it generally does not exceed 1% of the central value. The jittered PRI is centered on a value \(PRI_{c}\) and changes within the range of this value. The mathematical model is \(PRI=PRI_{c}+\sigma_{i}\)where \(\sigma_{i}\in[-\epsilon,\epsilon]\), \(\epsilon\) is the amount of jitter, the jitter rate is \(\delta\), and the general jitter rate is \(\delta\in[5\%,30\%]\). The staggered PRI means there are two or more fixed \(PRI_{i}\) values in a radar emitter, and each \(PRI_{i}\) is called its sub-period. In the last few decades, many scholars have made contributions in the field of radar signal deinterleaving. They proposed many classical algorithms to make the deinterleaving system more robust, accurate and intelligent. They are pushing forward the field of radar signal deinterleaving. In the 1970s, [PERSON] [7] proposed a template-matching method based on the actual space electromagnetic situation. First, the database of the main characteristic parameters of the radar emitter is established in advance, and then, the PDW of the received pulse signal is measured and compared with the database. This method achieved a good sorting effect when the electromagnetic environment was simple and the radar modulation modes were relatively fixed. In [8], the method of impulse heuristic search was proposed. First, assuming the base TOA and reference TOA in a pulse stream, the difference between the two pulses is obtained. After considering the actual error, it is judged whether the pulse difference is within the allowable error range to complete the deinterleaving. This method requires a lot of prior knowledge. To have a high search accuracy, the key is how to accurately find the potential PRI from the pulse stream. Some scholars have conducted a lot of work on this issue, mainly focusing on the method of PRI histogram. The cumulative difference histogram (CDIF) proposed in [13] and the sequential difference histogram (SDIF) proposed in [14] are representative of histogram methods. CDIF is an improvement of the traditional histogram method. It combines the traditional histogram with sequence search to suppress the generation of harmonics, but it needs to accumulate the statistical difference histograms, which require a large amount of calculations. CDIF has a threshold judgment before pulse search, and the threshold function is Equation (1). \[f_{CDIF}(\tau)=k\times\left(\frac{T}{\tau}\right) \tag{1}\]  
where \(T\) is the sampling time, and \(k\) is an adjustable parameter. Generally, \(k<1\), and \(\tau\) is the repetition interval. SDIF is an improvement of CDIF. The SDIF algorithm no longer accumulates the histogram, but directly compares the difference of the TOA sequence with the set threshold, which improves the efficiency of the deinterleaving algorithm. After the SDIF algorithm was proposed, it was widely used in the engineering of radar emitter signal deinterleaving. Equation (2) is the threshold function of the SDIF.