• Measurement and control distance: radius >5km (no shelter)
• Battery life (with load) : >30min
• Wind resistance (with load) : wind speed 13m/s
• Target positioning error: <10cm
• Target depth error: <20cm

1. Complex usage scenarios:
It can realize the detection and location of unexploded bombs in mountain, plain, shoal and other application scenarios.
2. Attitude interference compensation:
Compensating for the interference of the carrier makes the data acquisition of the detection system more accurate and reliable.
3. Automatic flight planning:
It can automatically detect tasks in the planned area after the planning is complete, improving work efficiency.
4. Real-time communication:
Stable transmission of magnetic anomaly coordinates within a 5km range meets the requirements of real-time detection and positioning.
5. Quick and easy installation:
The system uses a quick disassembly portable structure, which can be assembled and tested within 10 minutes by one person.
6. Integrated display:
The aeromagnetic detection system can display scalar/vector magnetic field information, position information and altitude information.
7. Very low system noise:
The total field is filtered and calibrated by compensation, and advanced wavelet entropy denoising and detection algorithms are integrated.
8. Efficient data post-processing:
The post-processing imaging software can draw a magnetic map of the detection area in 5 minutes to obtain intuitive detection information.

1. What can it detect?
It can be used to detect large ferromagnetic objects, such as mining areas, cables, and various means of transport.
2. How is the detection capability?
Before compensation, the maximum linear scale of the ferromagnetic target is 4-6 times; Compensation will be made on this basis
Increase by about 30% (the increase effect depends on the condition of the detection area).
3. Calibration compensation method?
Using a combination of airborne rotation and FOM flight.
4. Detection resolution?
Through the calibration compensation algorithm, the system has very low system noise and can distinguish 2nT weak magnetic signal.
5. Ideal flying altitude?
Ideal weather conditions, as close as possible to the target area as long as the system is determined to be safe.
6. Can it be detected on water?
Yes, the medium does not affect the sensor operation or weaken the magnetic field strength.

Operating environment:
Windows11 Home Edition 22H2, display resolution 1920×1080, memory 8G or more, Intel(R) Core(TM) i5-8400@2.8GHz 2.81GHz.
How to use:
Connect the ground end data transmission module to the computer or PDA through the USB port, open the corresponding serial port, the detection system is powered on, and wait for the optical pump to preheat for 30 seconds before it can work normally;
By introducing the compensation coefficient, the real-time attitude compensation of the detected data can be realized, and the display can be synchronized with the original data.
By adjusting the window length of the drawing, the data amount of the data display window can be changed in real time, but the size of the window itself will not be changed;
Click the "Data file" button under file control to start recording data, and click "End entry" to end data entry. The naming rule of the data file is "year - month - day - hour - minute - second DataFusion.txt", or you can change the name yourself.

How to use:
Data import can choose to import compensation data, probe data, daily variation data, click the "select file" button, select the data file to import;
The data preprocessing can eliminate the dead zone outlier in the collected data.
The algorithm center solves and applies the attitude compensation coefficient to effectively compensate the carrier noise interference, and supports the compensation coefficient derivation.
Visualization can quickly draw the detection track, line magnetic anomaly, regional magnetic map, and accurately obtain the required information;
Based on the obtained geographic and magnetic field data, the "spatial interpolation algorithm" is applied to realize the spatio-temporal mapping imaging of latitude and longitude and magnetic field data, supporting the selection of fine areas for independent imaging, focusing on the magnetic field imaging of key areas.
Based on the "particle swarm optimization algorithm", the depth and position information of the target is retrieved, and the suspected target is identified and judged based on "deep learning".