Emitter based localization via Passive RF sensors
Source localization via passive RF sensors has been a point of interest in recent years, because of its wide area of applications such as surveillance, target tracking, navigation. Moreover, its significance in the so-called ELINT systems for the defense sector cannot be over-emphasized. Due to the
2025-06-28 16:32:23 - Adil Khan
Emitter based localization via Passive RF sensors
Project Area of Specialization Electrical/Electronic EngineeringProject SummarySource localization via passive RF sensors has been a point of interest in recent years, because of its wide area of applications such as surveillance, target tracking, navigation. Moreover, its significance in the so-called ELINT systems for the defense sector cannot be over-emphasized. Due to the passive nature of sensors being used, such systems do not respond back to any interrogation hence are untraceable making them suitable for defense systems.
Passive radio frequency (RF) emitter localization is important in intelligence, surveillance, and reconnaissance, as well as in public safety operations. In urban or indoor settings, RF emissions are observed after interactions with a complex reflecting environment. Our project aims at designing a prototype system to locate emitter.
In this project we will develop a prototype system for RF based emitter localization using multiple antennas, nodes and sensors. The system will be tested to locate the coordinates of emitter that transmits RF signals. Signals thus received will be used to extract required information that is coordinates of the target.
Signals transmitted by source are to be captured and their IQ samples are stored offline. Samples thus stored from multiple nodes which are time synchronized are used to calculate Cross Correlation to find time difference of arrival at different nodes. Afterwards the technique called TDOA is used to locate emitter.
MATLAB is used to extract IQ samples and further processing including cross correlation and TDOA realization.
Project ObjectivesWe aim to achieve the following objectives through this project:
- A prototype system of RF emitter localization Emitter will be localized using one of techniques & methods available for RF source localization.
- The system shall consist of passive sensors only, which do not embody any source of illumination.
- The system shall be able to estimate location of multiple emitters transmitting at different frequencies
- The system shall have a MATLAB based GUI for visualization.
- We aim to enhance our skills set in Signal Processing, Telecommunications, Embedded Systems, Microcontrollers and Machine learning for better job placements.
After thorough literature survey of the project we have identified the following implementation approach that is TDOA (Time Difference of Arrival):
- To start with TDOA, we need to have at least three tightly time synchronized systems placed at least a few kms apart from each other.
- Time synchronization will be achieved.
- The systems will be interfaced to signal acquisition cards with capability of capturing IQ signals at any designated centre frequency…
- IQ samples will be computed and used to perform cross-correlation giving us time difference of arrival of signal at multiple nodes
- The basic premise of TDOA is to measure the difference in time of arrival of a pulse at several sensor locations, and to use that measurement to compute the emitter’s position. This method does not require the time that the signal was sent from the target, only the time the signal was received and the speed that the signal travels. TDOA has the potential to provide very high accuracy at very long ranges.
- This technique involves sending signals between one target object and several fixed reference points called as receivers which will be synchronized with one another. The arriving signal sent from the unknown target will be received with some time delay at each sensor.
- When the signals will be received at each receiver they will be sent to a base station where they will be cross correlated and the time difference between the arrival of the signals will be calculated.
- Using that time difference and the distance formulas we can calculate coordinates of the target and plot hyperbolas. Where c is the speed of light. T is the time difference between two sensors. X1 and Y1 are the coordinates of the target and x2 and y2 are coordinates of receivers. The point where all hyperbolas intersect gives us our required position.
- This is the ideal case scenario. But in reality, no signal is received without noise. The factor of noise adds errors to the calculations and geometry of hyperbolas. Hence the hyperbolas will not intersect at one single point but all of them will intersect at different points giving us an estimated region where our target lies.
- By using some algorithms and mathematical techniques such as least square, maximum likelihood we can minimize the error to some extent. And present precise region according to some percentage.
- To broaden the scope of our project, we will design a MATLAB based Graphical User Interface.
This project will give the following benefits in solving the real world problems:
- This project aims to implement RF emitter localization via state of the art TDOA algorithms. It is helpful in intelligence, surveillance, and reconnaissance, as well as in public safety operations.
- Due to the passive nature of the used RF sensors such systems cannot be traced and are efficient in defense sector.
- Its significance in target tracking, surveillance and position-detecting applications for defense cannot be over emphasized. Keeping in view, this significance, the Center for Advanced Research in Engineering, has offered us full support in using their guidance and facilities for completion of the FYP.
- At individual level, the project will provide us a hands-on experience of designing a prototype ELINT system from scratch. We already learned a lot of new concepts of this domain.
At the completion of our project, we will provide the following deliverables:
- A prototype system of source localization that can capture RF signals transmitted from source and extract IQ samples.
- Post-processing of IQ samples captured at multiple nodes in an offline manner to perform cross-correlation and find time difference of arrival of signal at the various nodes
- Implementation of TDOA algorithm for estimating the co-ordinates of the unknown emitter
- A MATLAB based Graphical User Interface for better visualization of results.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 69200 | |||
| Bn220_GPS Dongle for time synchronization at each sensor node | Equipment | 3 | 3400 | 10200 |
| Raspeberry Pi 3_To provide serial communication | Equipment | 3 | 9000 | 27000 |
| RTL-SDR_Receives FM signals for processing | Equipment | 3 | 8000 | 24000 |
| Poster Priniting | Miscellaneous | 1 | 8000 | 8000 |