Real-time passive
sonar deployment tool
Real-time passive sonar deployment tool
The passive sonar deployment, typically presents two critical requirements, namely detection of an adversary and evade detection by an adversary. In a battlefield, these two requirements are an ever evolving requirements and thus require real-time situational awareness, so that the platform can maneuver and position itself appropriately. The Source-Path-Receiver model is the key to such an effort and it has to take into account the site specific local ground realities. The tropical littoral waters of the Indian Ocean Region (IOR) and the South China Sea (SCS) present very unique challenges for any sonar operator. In the proposed Real Time Passive Sonar Deployment Tool (RPSDT), we will attempt to address the challenges and opportunities of undersea deployments from an operational perspective.
The Signal to Noise Ratio (SNR) is the key parameter to ascertain the detection performance of the sonar at the deployment location. The signal strength may not be in our control, however selection of the deployment location with least ambient noise could enhance the SNR and corresponding detection capability. The operational commander can choose the appropriate the deployment location based on the minimal SNR value within the operations area to ensure effective detection. The dynamic SNR computation will take into account the real-time spatio-temporal low frequency ambient noise mapping based on the local underwater medium fluctuations.
The own acoustic signature propagates outward and is a measure of our vulnerability to detection by our adversary in the backdrop on the SNR at the potential location of their deployment. Thus, the assessment of the transmission loss across the local channel and its bench marking against the SNR at their deployment location will provide an effective measure of the vulnerability. Compared to the above case, the signal in the SNR computation will be the own radiated noise and the ambient noise measurement is at the receiver location of the potential adversary.
The submarine commander may have to balance between enhancing detection effectiveness of their own sensors and minimizing vulnerability of the own platform based on the inputs provided by the RPSDT. The proposed RPSDT will be an effective tool, independent of the on-board sonar that will facilitate effective operational deployment of the platform in any operational area anchored to the ground realities in real-time.
- Real-time SNR assessment for effective deployment of the passive sonar.
- Real-time underwater acoustic propagation characterization for effective evaluation of the sonar parameters.
- Customized, user specific GUI for seamless usage, even on hand held devices.
- Deployment of deep-learning algorithms to mitigate errors during offline mode.
- Site-specific sourcing of input parameters to formulate modelling and simulation algorithms for realistic assessment of the sonar performance.
- Real-time SNR assessment for effective deployment of the passive sonar.
- Real-time underwater acoustic propagation characterization for effective evaluation of the sonar parameters.
- Customized, user specific GUI for seamless usage, even on hand held devices.
- Deployment of deep-learning algorithms to mitigate errors during offline mode.
- Site-specific sourcing of input parameters to formulate modelling and simulation algorithms for realistic assessment of the sonar performance.
The passive sonar operate in the low frequency below 1 kHz that is dominated by the ambient noise generated by distant shipping. The Automatic Identification System (AIS),provides the spatio-temporal variation of the shipping traffic globally and this can be an important input for radiated noise computation at source. The entire region of interest, is divided into square grids of size equivalent of the smallest unit of latitude and longitude.Radiated noise estimation using Modelling and Simulation (M&S) algorithms to ascertain the noise at source in each of the grids is computed. The source noise is coupled with the transmission loss across the underwater channel to obtain the radiated noise at the receiver location.
The site specific tropical littoral acoustic propagation characteristics is mapped using the real-time local parameters of the underwater channel. These include surface parameters, Sound Velocity Profile (SVP), bottom type & bathymetry and more from open source databases meant for weather monitoring. The Underwater Channel model representing the path of the radiated noise provides very accurate transmission loss at the site of the sonar deployment for realistic assessment of the degradation of the acoustic signature for both effective detection and also vulnerability assessment. In the case of non-availability of the real-time parameters, intelligent guess can be made using historical databases and deep-learning techniques.
The varied parameters at the receiver location depending upon the application (effective detection or vulnerability assessment) will be presented. These could include SNR, detection range, vulnerability assessment and more in a 3D map will substantially enhance our operational appreciation of the tactical situational awareness. The mapping will take real-time inputs and provide site specific local inputs for implementation of the M&S algorithms. The Graphic User Interface (GUI), will provide the inputs as per the user requirement. A hierarchical information system will be designed to manage the operational requirement for the operator, local commander, platform in-charge or even other senior operational commanders at multiple levels. Customized hand held displays will be provided independent of the sonar on-board.
The Signal to Noise Ratio (SNR) is the key parameter to ascertain the detection performance of the sonar at the deployment location. The signal strength may not be in our control, however selection of the deployment location with least ambient noise could enhance the SNR and corresponding detection capability. The operational commander can choose the appropriate the deployment location based on the minimal SNR value within the operations area to ensure effective detection. The dynamic SNR computation will take into account the real-time spatio-temporal low frequency ambient noise mapping based on the local underwater medium fluctuations.
The own acoustic signature propagates outward and is a measure of our vulnerability to detection by our adversary in the backdrop on the SNR at the potential location of their deployment. Thus, the assessment of the transmission loss across the local channel and its bench marking against the SNR at their deployment location will provide an effective measure of the vulnerability. Compared to the above case, the signal in the SNR computation will be the own radiated noise and the ambient noise measurement is at the receiver location of the potential adversary.