# mantis-2024-aess-challenge

**Repository Path**: tekdf/mantis-2024-aess-challenge

## Basic Information

- **Project Name**: mantis-2024-aess-challenge
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-07-05
- **Last Updated**: 2025-07-05

## Categories & Tags

**Categories**: Uncategorized

**Tags**: 相控阵雷达

## README

# mantis-2024-aess-challenge

Welcome to the repository for the [Mantis team](#team) for the 2024 IEEE AESS Radar Challenge.

## Mission

Inverse Synthetic Aperture Radar, ISAR, is a technique for creating images from radar data. ISAR is similar to SAR in that it employs relative motion between a radar and targets or scenes to form large synthetic apertures leading to fine azimuthal resolution. SAR and ISAR differ in that ISAR uses a stationary radar to image moving targets, while SAR uses radar motion to image (typically) stationary scenes. While SAR can typically take advantage of onboard sensors for motion estimation of the radar platform, such as a GPS or INS, ISAR must use various signal processing techniques to estimate, compensate, and take advantage of target motion.

We created an ISAR system that can be placed onshore and act as a low-cost monitoring system for an onshore team looking to observe water traffic. The benefit of this system over an optical system is that it works even in poor visibility conditions, such fog and darkness. It also has the potential to extend into a classification system, where it identifies the type of boat being tracked.

To take advantage of the Phaser CN0566 for a FMCW radar, we used a 500 MHz bandwidth chirp generated by the onboard ADF4159 synthesizer (swept from 12.0 to 12.5 GHz) and 2.15 GHz IF. Transmit from the PLUTO-SDR a positive 500kHz tone at the 2.2 GHz IF with 9.85 – 10.35 GHz chirp at the RF output. The transmit antenna was set up forward of the receive array for as much direct-path isolation as possible. Receive data was be calibrated, channel-summed, and packetized based on triggering from the logic interrupt of the ADF4159, and made available for archive off-device.

The radar system engineer’s role is to identify and consider a large trade-space of possibilities and we found that the CN0566 kit could be used for our system despite some obvious and not-so-obvious limitations. The primary concern to consider is that for scanning in azimuth, the radar operates with a vertical polarization and that this is typically avoided for sea operations as the clutter return is higher for low grazing angles. In our use case, we will only rarely encounter significant sea-states and high-winds, therefore the polarization issue of sea clutter will be suppressed. A second limitation is the bandwidth of the receiver, both in maximal bandwidth of the PLUTO-SDR’s AD9363 as well as streaming USB data rates. Both of these bandwidth limitations cause concern, the first limiting the resolvable target velocity and the second reducing average power for a continuous or almost-continuous radar. Ultimately, for our test location, our clutter cross-section was low and target cross-section was high, as well as along-range velocity was low.

Check out a video demo of our project [here](https://youtu.be/eVkxuBhQILY).

Data is linked [here](https://drive.google.com/drive/folders/11EBF_MmQtxgatDQYX_4F9UndbK7i9hd4?usp=sharing) and [here](https://drive.google.com/drive/folders/1g3vTsPNC97ftYrKXICPYV_rrJ66MP6kf?usp=sharing).

## Team

The Mantis team is affiliated with the University of Washington Applied Physics Lab in Seattle, Washington.

### Dylan Wesen

> Dylan Wesen is first-year mechanical engineering graduate student at the University of Washington, studying control systems, vibrations, and acoustics. While in undergrad, he assisted in the designing and testing of sonar systems with the University of Washington Applied Physics Lab. His current research explores novel array designs for remote sensing and communications.

### Nicole Pham

> Nicole Pham is a first-year electrical engineering graduate student at the University of Washington. Her background includes an electrical engineering degree with a concentration in control theory from the University of Washington in 2022 and work experience as a systems engineer in medical devices. Her research interests are in signal processing, machine learning, and FPGAs.

#### Mentor
#### John Mower

> John Mower received his BSEE and MSEE degrees from the University of Washington, (2010 and 2012), where he studied electromagnetics and millimeter-wave remote sensing. He is currently a Senior Research Engineer at the Applied Physics Laboratory – University of Washington. His current work includes RF and acoustic communications and remote sensing. Always happy to discuss radar, radio, acoustics, and remote sensing, he can be reached at mowerj@uw.edu.