EXPLANATION OF MULTIPLE TRACKING TARGETS IN MTI RADAR AND ITS FILTERING WITH KALMAN MODEL AND IMM ALGORITHM

Since the tracking of moving targets is a fundamental concern in military and civilian applications, aerospace industries are always studying for exact, low-error, computationally light, and uncomplicated algorithms for target tracking. Nowadays, most modern military systems are equipped with numerous sensors. The perfect operation of such sensors helps to achieve target tracking. Due to the nature of the sensor system and the types of noises, one kind of sensor alone cannot be perfectly used in target tracking. Consequently, several different sensors are operated in new systems for tracking. The present study aims to explain the multiple tracking targets in MTI radar and its filtering with the Kalman model and IMM algorithms. Also, applied algorithms for tracking moving targets using phased array radar are discussed. Various algorithms are proposed in this field, including interacting multiple models (IMM), Kalman filter (KF), and extended Kalman filter (EKF). These simple and multi-rate algorithms are reviewed in detail.

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Publication Details

Journal
TMP Universal Journal of Research and Review Archives.
Published
2024-12-01
DOI
https://doi.org/10.69557/ujrra.v3i4.128
Primary Topic
Target Tracking and Data Fusion in Sensor Networks
Type
article
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article

EXPLANATION OF MULTIPLE TRACKING TARGETS IN MTI RADAR AND ITS FILTERING WITH KALMAN MODEL AND IMM ALGORITHM

Hajar Godarzi
TMP Universal Journal of Research and Review Archives.
Target Tracking and Data Fusion in Sensor Networks
article

EXPLANATION OF MULTIPLE TRACKING TARGETS IN MTI RADAR AND ITS FILTERING WITH KALMAN MODEL AND IMM ALGORITHM

Hajar Godarzi
article en

Abstract

Since the tracking of moving targets is a fundamental concern in military and civilian applications, aerospace industries are always studying for exact, low-error, computationally light, and uncomplicated algorithms for target tracking. Nowadays, most modern military systems are equipped with numerous sensors. The perfect operation of such sensors helps to achieve target tracking. Due to the nature of the sensor system and the types of noises, one kind of sensor alone cannot be perfectly used in target tracking. Consequently, several different sensors are operated in new systems for tracking. The present study aims to explain the multiple tracking targets in MTI radar and its filtering with the Kalman model and IMM algorithms. Also, applied algorithms for tracking moving targets using phased array radar are discussed. Various algorithms are proposed in this field, including interacting multiple models (IMM), Kalman filter (KF), and extended Kalman filter (EKF). These simple and multi-rate algorithms are reviewed in detail.

TMP Universal Journal of Research and Review Archives.Vol. 3(4)
Openalex Percentile: Top 76%
Target Tracking and Data Fusion in Sensor Networks
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EXPLANATION OF MULTIPLE TRACKING TARGETS IN MTI RADAR AND ITS FILTERING WITH KALMAN MODEL AND IMM ALGORITHM — Hajar Godarzi · TMP Universal Journal of Research and Review Archives. (2024) | TGRS Research Map | TGRS