Prediction of Aircraft Trajectory Based on Mogrifier-BiGRU

doi:10.12382/bgxb.2022.0750

Abstract

Abstract:

For the low accuracy of trajectory prediction of current aircraft, the bidirectional propagation mechanism and Mogrifier data coupling module are introduced to improve the gated recurrent unit (GRU) network. A prediction algorithm of aircraft trajectory based on Mogrifier-BiGRU is proposed, which strengthens the learning and memory of historical data, makes the input information fully coupled with the hidden layer data, and improves the prediction accuracy. The simulated results show that the accuracy of the proposed method for predicting the aircraft maneuver trajectory can reach 96.26%, which meets the actual demand of combat commanders for accurate prediction of battlefield situation.

Key words: trajectory prediction, bidirectional gated recurrent unit, Mogrifier data module, deep learning

CLC Number:

E926

ZHANG Kun, DU Ruiyi, SHI Haotian, HUA Shuai. Prediction of Aircraft Trajectory Based on Mogrifier-BiGRU[J]. Acta Armamentarii, 2024, 45(2): 373-384.

Figures/Tables 19

References 27

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模型	r	平均准确率/%	平均偏差率/%
	0	86.24	13.81
	1	88.50	10.97
	2	86.18	14.96
	3	88.98	12.35
	4	86.61	14.92
Mogrifier_BiGRU	5	87.70	13.16
	6	88.25	11.10
	7	87.95	13.04
	8	88.50	12.33
	9	86.95	12.25
	10	86.48	14.97
	20	83.64	13.98
Multiplicative_BiGRU		86.13	13.13

模型	r	平均准确率/%	平均偏差率/%
	0	86.24	13.81
	1	88.50	10.97
	2	86.18	14.96
	3	88.98	12.35
	4	86.61	14.92
Mogrifier_BiGRU	5	87.70	13.16
	6	88.25	11.10
	7	87.95	13.04
	8	88.50	12.33
	9	86.95	12.25
	10	86.48	14.97
	20	83.64	13.98
Multiplicative_BiGRU		86.13	13.13

网络参数	取值	网络参数	取值
飞行器轨迹数据量	1000	训练回合	50000
η	0.8	ε	0.05
采样时间间隔/s	0.25	GRU网络层数	3
r	1	GRU网络隐藏节点数	256

网络参数	取值	网络参数	取值
飞行器轨迹数据量	1000	训练回合	50000
η	0.8	ε	0.05
采样时间间隔/s	0.25	GRU网络层数	3
r	1	GRU网络隐藏节点数	256

网络	平均准确率/%	平均偏差率/%
GRU	26.50	20.19
BiGRU	85.93	12.05
BiLSTM	85.20	12.17
Multiplicative_BiGRU	91.42	8.20
Mogrifier_BiGRU	94.40	4.74