Aerospace and Electronic Systems Magazine July 2018 - 42

Hybrid Guidance System Based on Infrared and Millimeter Waves

Online Learning Strategy
Target tracking based on self-learning
is performed using a tracking module, a learning module, and a detection
module. The tracking module is used to
determine the tracking position of the
target. The learning module is trained
and updated online according to feature
information and classifier updating. In
addition, the learning module can provide a sample library that can be used
to determine a target type. The results
obtained by online learning are then
transmitted to both the tracking module
and the detection module to correct the
tacking deviation. The detection module inputs are current regional features
from the classifier, and the outputs of
the detection module are inputs for the
learning module; thus, the classifier can
achieve online learning and update the
target state changes.

Online Sample Preparation Method
The sample library of the classifier is
obtained by cyclic shifting of images of
the target position. The images obtained
by cyclic shifting are not smooth at the
boundary, so multiplying the Hanning
window can reduce the weight of the
image edge [22]. Thus, high-frequency
interference can be eliminated.

Figure 13.

Schematic diagram of SLB and SLC in a phased array.

Recapture Technology after Target Loss
The target loss problem after jamming can be solved in two ways.
On the one hand, real-time prediction of target trajectory and state
change using obtained target information determines the direction
and target speed in the tracking process; thus, it adjusts the imager
view field effectively. On the other hand, the target-tracking algorithm based on self-learning provides real-time acquisition and
updates target feature information; meanwhile, it provides efficient
long-term tracking and has the ability to recapture the lost target.
Therefore, the infrared image tracking performance is more stable
and reliable.

ANTIJAMMING TECHNOLOGY IN A MILLIMETER WAVE
ACTIVE PHASED ARRAY DETECTOR
To ensure proper operation of the millimeter wave detection system, the strong interference signals should be mitigated in radar
echo signal processing. The basic aim is to restrain the interference
from the airspace, and the specific plan is to control the antenna to
achieve anti-interference. In the millimeter wave detection system,
both side-lobe blanking (SLB) and side-lobe cancellation (SLC)
42

are used to restrain interference, and a flowchart of the process
used when these methods are combined is shown in Figure 13.
In the signal processing module, a continuous interference
can be canceled by a cross-correlation calculation in a specific
distance gate. After the cancellation process and pulse compression, the results of SLC and SLB are transmitted to the comparator to determine whether there is a need to turn off the receiving
units so that the pulse interference can be reduced. In addition,
the completion of SLB system function is conducted on a single
distance unit. Moreover, cell alignment plays a key role in interference reduction.

ANTIJAMMING TECHNOLOGY BASED ON FUSION OF
INFRARED AND MILLIMETER WAVES
In a real battlefield environment, missiles might be subjected to
different types of interference. Consequently, the target information obtained by the millimeter wave detection system and the
infrared imaging system might be inaccurate [22]. To ensure the
reliability of the tracking system, the target state is estimated using
target observation by the infrared tracking system and according to
the interference.

IEEE A&E SYSTEMS MAGAZINE

JULY 2018

Table of Contents for the Digital Edition of Aerospace and Electronic Systems Magazine July 2018