See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/353515556 Modelling of Radar Targets and Radar Cross Section For Air Traffic Control Radars Article · July 2021 CITATIONS READS 10 126 2 authors: QAYSAR Salih Mahdy Ganesh Babu Loganathan Tishk International University - Erbil Tishk International University iraq 107 PUBLICATIONS 66 CITATIONS 120 PUBLICATIONS 2,156 CITATIONS SEE PROFILE SEE PROFILE Some of the authors of this publication are also working on these related projects: Development of a Novel Solar Cooker using Nanomaterials Enhanced Phase Change Materials (NEPCMs) Integrated with Water Heater View project Smart Agriculture System With E – Carbage Using Iot View project All content following this page was uploaded by Ganesh Babu Loganathan on 28 July 2021. The user has requested enhancement of the downloaded file. Efflatounia ISSN: 1110-8703 Pages: 664 – 674 Volume: 5 Issue 2 Modelling of Radar Targets and Radar Cross Section For Air Traffic Control Radars 1Dr.Qaysar Salih Mahdi, 2Mr.Ganesh Babu Loganathan ITServices Department/Rectorate,Tishk International University,Erbil,Kurdistan,Iraq 2 Assistant Professor, Mechatronics Engineering, Tishk International University,Erbil, Kurdistan, Iraq Email ID:[email protected], [email protected] 1 Abstract—This paper studies the effect of target fluctuating models on ATC radar coverage such as swerling`s models 1 and 2, and swerling`s models 3 and 5. The results in this work show that swerlings case 5 (non-fluctuating target) has the highest range and swerling case 2 (fluctuating target) has higher range than swerling case 1 (fluctuating target). The signal to noise ratio obtained are claimed to be accurate to within 1dB for values of Hs >100. The deviation from the exact values of the signal to noise ratio for Hs <100 is rather large. It may be reduced, however, to acceptable values by using certain correction of the swerling models and acceptable improvements in the SNR is obtained. The applications of this work sound widely espacially for ATC radar systems and militery applications for target classification and recognition. This work is performed by using C++ and object oriented programming and it could be used as a prediction package in the ATCR sitting. Keywords; ATC radar; fluctuating targets; swerling`s models; SNR I. INTRODUCTION The differentiation between fluctuating and non-fluctuating targets is of essential target in the processing of radar target classification [1-3,15-24]. The non-fluctuating target would yield target echoes of constant amplitude which is valid only for a very limited range of time [4, 7-14]. Since real targets e.g., aircraft and ships, consist of a large complex structure with small features which will cause multiple reflections of the impinging electromagnetic radiation [6, 25-41]. Therefore, if a target in motion, the echo signal is never constant [1,5, 42-59]. II. THEORETICAL PRINCIPLES A. SNR Signal To Noise Ratio The signal to noise ratio (SNR), requested to guarantee a certain value of probability of detection, differentiate between fluctuating and non-fluctuating targets [6,4]. The non-fluctuating target would yield target echoes of constant amplitude which is valid only for a very limited range of targets while fluctuating targets yield targets of variable amplitude [60-67]. A popular method for representing the fluctuations of targets is the four statistical models described by Peter Swerling [1]. For each of these he calculated the signal to noise ratio (SNR) as required, as a function of the probability of detection, probability of false alarm and the number of pulses integrated. 664 Website: www.efflatounia.com Efflatounia ISSN: 1110-8703 Pages: 664 – 674 Volume: 5 Issue 2 B. Swerling`s Models Improvements Five swerling`s models are studied and improved in this study and are introduced to classify the radar targets types, these models and their corrections are discussed below. 1) Swerling`s fluctuating case 1 The SNR is given by; (P SNR = −1 Hs ln fa ) 1 P . (1) Similar to the non-fluctuating target case 5, a correction factor is introduced and is given by; d CSW1= 0.06245*ln2(Hs)–0.572*ln(Hs) + 2.435. (2) 2) Swerling`s fluctuating case 2 The SNR is given by; SNR = 2[ −1 ( P fa) − −1 ( P d )] Hs . and similarly a correction factor is introduced and is given by; CSW2=0.03681*ln2(Hs)–0.40362*ln(Hs)+ 2.25712. (3) (4) 3) Swerling`s fluctuating case 3 The SNR is given by; SNR = 4 −1 ( P fa) Hs M . (5) Where M is given by; M = 3.11573–3.48772*Pd+0.26522*Pd2 + 0.11477/Pd (6) and similarly a correction factor is introduced and is given by; CSW3= 0.00052*ln2(Hs) – 0.16429*ln( Hs) + 1.93131. (7) 4) Swerling`s fluctuating case 4 The SNR is given by; SNR = 2[ −1 ( P fa) − −1 ( P d )] Hs (8) and similarly a correction factor is introduced and is given by; CSW4=0.05981*ln2(Hs)–0.63253*ln(Hs)+2.80934. (9) 5) Swerling`s non-fluctuating case 5 This model needs no correction because the amplitude of the echo signal is constant. C. Radar Target Direction 665 Website: www.efflatounia.com Efflatounia ISSN: 1110-8703 Pages: 664 – 674 Volume: 5 Issue 2 Once a target is detected, the next step is to pinpoint the precise location of a target. This position provides the userwith the distance(range) to the target and its direction. • Range: The distance to a target is determined by measuring the round trip transit time of the signals between the radar and the target. • Direction: For most radars, the direction to a target is measured in terms of the angle between the line of sight to the target and some reference coordinate system. Most of the time, this angle is divided into its horizontal (azimuth) and vertical (elevation) components and are measured based on the direction where the antenna is pointed see Fig. (1). By knowing the range and direction of a target, a radar system can use this information to track the target location as needed. Figure 1. Target position determination III. MODELING AND SIMULATTION A. Radar Coverage In the present work the effects of the fluctuating and non fluctuating targets models and their corrections on the radar coverage are studied in addition to the RCS and PRF. The algorithm steps for the radar coverage was explained by [ 3,7 ]. B. ATCR Radar Parameters The ATCR radar systam which its coverage is modeled using computer simulation, has the following parameters presented in Table 1. TABLE 1. ATCR RADAR PARAMETERS Frequency Horizontal Beam Width Vertical Beam Width Tilt Revolution Per Minute (RPM) Transmitter Peak Power Receiver noise figure Receiver Bandwidth Intermediate frequency of the receiver 1300 MHz 1 6 0 5 r.p.m. 2200 kW 4.5 dB 0.6 MHz 30MHz 666 Website: www.efflatounia.com Efflatounia ISSN: 1110-8703 Pages: 664 – 674 Volume: 5 Issue 2 Pulse Repetition Frequency (PRF) Probability of False Alarm, Pfa Probability of Detection, Pd 400 Hz 10-6 80% Plumbing and transmission line losses 12 dB Aerial height 19 m Radar Cross Section , RCS () IV. A. 2 m2 RESULTS AND DISCUSSION The effects of target fluctuating models on radar coverage The effects of target fluctuating models on the radar coverage are shown in Fig. 2 (sweling case 1 and 5 ) and Fig. 3 (swerling case 1 and 2). It can be noticed that swerling case 5 (non-fluctuating target) has the highest range. Swerling case 2 (fluctuating target) has higher range than swerling case 1 (fluctuating target). Figure 2. Effects of swerling cases 1 & 5 Figure 3. Effects of swerling cases 1 & 2 B. The effect of RCS on radar coverage The effect of radar cross section is shown in Fig. 4 where 2 sections are taken 10 and 15 m . The higher cross section has higher range. two radar cross 667 Website: www.efflatounia.com Efflatounia ISSN: 1110-8703 Pages: 664 – 674 Volume: 5 Issue 2 Figure 4. Effects of radar cross section C. The effects of PRF on radar coverage The effects of changing the PRF on radar coverage are presented (two PRFs 100Hz and 1000Hz) in Fig. 5, where it can be noticed that the higher PRF has higher range, because of the increase in the number of transmitted pulses and hence increasing the number of hits per scan[8]. Figure 5. Effects of PRF V. CONCLUSIONS Classification of radar targets into four models such as swerling 1,2,3, and 4 are studied in order to simulate their improvement on the probability of detection and the radar range and it is concluded that swerling case 5 (non-fluctuating target) has the highest range. Swerling case 2 (fluctuating target) has higher range than swerling case 1 (fluctuating target). Also it is concluded that the fluctuating targets having lower detection ranges than the non-fluctuating targets which is noteced in Figs. 2 and 3, because manouvering of the fighters in speed which affects the signal to noise ratio. Also it can be concluded that large targets such as transportation aeroplain requires higher signal to noise ratio than small targets such as fighters . Also the other factor which affecting the signal to noise ratio is the PRF parameter which increasing the radar range when it is increased from 100Hz to 1000Hz and acceptable improvement in the SNR is obtained. 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