Dönüştürülmüş ölçümler Kalman filtresi tabanlı skalerle ağırlıklandırılmış etkileşimli çoklu model

Bu çalışmada hedef takibi için, füzyon kriterlerine dayalı Skalerle ağırlıklandırılmış Etkileşimli Çoklu Model (SIMM) algoritması ile koordinat dönüşümlerinden kaynaklı sapmanın azaltılmasına yönelik öne sürülen Dönüştürülmüş Ölçümler Kalman Filtresi (CMKF) algoritması özelliklerinden yararlanılarak birden fazla hedef hareket modelinin kullanımına olanak sağlayan yeni bir Etkileşimli Çoklu Model (IMM) algoritması önerilmiştir. Önerilen algoritma yoğun manevralı ve yoğun gürültülü senaryolarda test edilmiştir. Önerilen algoritmanın, ölçümlerin polar/küresel koordinat olması durumunda literatürdeki SIMM-KF ve IMM-CMKF algoritmalarından daha az mesafe hatasına sahip olduğu gösterilmiştir.

Scalar-weight interacting multiple model based on converted measurements Kalman filter

In this study, we take advantage of the fusion criteria based- Scalar-weight Interacting Multiple Model (SIMM) algorithm and the Converted Measurements Kalman Filter (CMKF), which reduces the bias caused by coordinate transformations to propose a novel Interacting Multiple Model (IMM) tracking algorithm which uses multiple motion models for target tracking, The proposed algorithm has been tested on scenarios with highly maneuvering targets under heavy measurement noise. It is shown that the proposed algorithm has smaller estimation error compared to SIMM-KF and IMM-CMKF algorithms.

Kaynakça

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