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SIH26058HardwareRobotics and Drones
₹1,50,000 Prize (₹75k Joint)
•
Deadline: 20 September 2026
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Submitted Ideas: 0/500

Development of a Low-Power, Real-Time Adaptive Software-Defined Sonar Transmitter Payload for Autonomous Underwater Vehicles (AUVs)

Ministry / Organization: Ministry of Earth Sciences (MoES)
Department: National Institute of Ocean Technology (NIOT)
SIH Official Portal
Technical Complexity
9/10
Dataset Accessibility
8/10
36h Hackathon Viability
8/10
Step 0 • Zero-Jargon Layman Summary

“Underwater robots (AUVs) need sonars to map the ocean floor, but water conditions like turbidity or temperature distort sound waves. This project builds a smart transmitter hardware payload that automatically adjusts its sound pulses in real-time based on environmental conditions to save battery and optimize image quality.”

The DecodeX PS Decoder™

Deconstructed Problem Blueprint

Step 1

WHAT TO BUILD?

A physical, low-power Software-Defined Sonar Transmitter payload module built using an embedded microcontroller (e.g., STM32/ESP32/FPGA), DAC, analog filters, and environmental sensor inputs.

Step 2

WHO IS IT FOR?

Ministry of Earth Sciences (MoES), National Institute of Ocean Technology (NIOT), and marine researchers/engineers operating Autonomous Underwater Vehicles (AUVs).

Step 3

WHY DOES IT EXIST?

Traditional sonars use fixed-frequency pulses that either scatter instantly in murky waters or yield blurry images, and they fail to adapt to changing underwater environments, resulting in wasted battery and poor marine mapping data.

Step 4

INPUT → PROCESS → OUTPUT ARCHITECTURE PIPELINE

01 • Inputs & Telemetry

Real-time environmental sensor data (temperature, turbidity, salinity) or simulated analog voltage inputs via potentiometers read through an ADC.

02 • Processing & AI Core

Microcontroller computes optimal wave parameters (bandwidth, duration, amplitude), applies digital windowing functions, and streams waveform data using Direct Memory Access (DMA) and hardware timers to a DAC.

03 • Actionable Deliverables

Clean, optimized physical analog LFM chirp/sweep waveforms outputted via an op-amp circuit, validated on an oscilloscope and FFT spectrum analyzer.

Step 5

CONSTRAINTS

  • Must be low-power to protect AUV battery packs
  • Must perform real-time wave synthesis without CPU stalling
  • Must include physical analog signal conditioning filters to eliminate sidelobe artifacts
  • Must fit inside a rugged, field-deployable payload pod enclosure
Step 6

JURY METRICS

  • Oscilloscope waveform integrity and low harmonic distortion
  • FFT spectrum accuracy
  • Responsiveness of waveform adaptation to changing sensor inputs
  • Power efficiency and hardware-level optimization via DMA/timers
Step 7

CORE BOTTLENECK

Configuring low-level peripherals (DMA and hardware timers) on the microcontroller to stream high-frequency waveform arrays smoothly to the DAC without lagging or crashing the CPU.

Why You Should Choose This PS (Pros)

  • Highly tangible hardware demo that looks incredible on the judging table with an oscilloscope
  • Directly addresses critical real-world NIOT requirements for marine robotics
  • Clear, modular breakdown of firmware, analog frontend, and mechanical enclosure

Challenges & Risks to Watch (Cons)

  • Requires actual hardware debugging, oscilloscopes, and analog circuitry during the hackathon
  • Risk of hardware component failure or signal noise during live evaluation
  • Steep learning curve for low-level DMA and timer register configurations
Hackathon Blueprint

Recommended Tech Stack & Grand Finale Features

Frontend & Mobile
Embedded GUI / Serial Plotter Dashboard (Python/PyQt)
Backend & APIs
C/C++ using STM32CubeIDE or ESP-IDF
AI / ML & Models
None required (pure deterministic embedded signal processing)
Database & Cloud
Local Flash Memory for waveform lookup tables (LUT)

Killer Features to Impress the SIH Jury

Pre-computed Lookup Tables (LUTs) with DMA streaming for zero CPU lag during waveform generation
Dynamic switching between LFM Chirps, Geometric Sweeps, and Phase-Coded Pulses instantly via potentiometer triggers
Real-time visual telemetry dashboard on a laptop via UART showing current bandwidth, frequency, and power parameters
Compact 3D-printed modular payload housing designed to fit standard AUV hull slots
View Official SIH 2026 Portal Raw Text
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•Background In underwater exploration and marine mapping, Autonomous Underwater Vehicles (AUVs) rely heavily on side-scan sonar systems. The performance of these systems is entirely dependent on the physical characteristics of the transmitted acoustic wave, known as the ‘ping’. Traditional sonars transmit short, fixed-frequency pulses. However, modern advanced military and research systems utilize Linear Frequency Modulated (LFM) Chirps—waveforms that sweep across a spectrum of frequencies over a precise timeframe.The primary bottleneck is that the underwater environment is highly dynamic. Sound waves behave differently depending on water depth, turbidity (suspended mud/sediment particles),temperature, and salinity. A high-frequency chirp (500 kHz) offers ultra-high image resolution but scatters instantly in muddy or deep waters. Conversely, a low-frequency chirp (100 kHz) can penetrate murky water and travel long distances but yields a blurry, low-resolution image. For an AUV to map effectively without draining its limited battery payload, its transmitter hardware must behave like a Software-Defined Radio (SDR)—dynamically adapting its physical analog pulse waveform in real-time based on the actual environmental conditions it encounters.
•Description Participants must design, prototype, and demonstrate a physical, self-contained Software-Defined Sonar Transmitter Payload Module.Instead of a software simulation, the solution must be a physical hardware unit built using an embedded platform (e.g., STM32, ESP32, Texas Instruments DSP, or an FPGA) integrated with custom analog electronics. The hardware must ingest real-time environmental data (via physical sensors, or analog voltage dials acting as sensor inputs) and mathematically synthesize and output an optimized, real-time physical analog waveform via a Digital-to-Analog Converter (DAC) and amplifier circuit.The entire hardware architecture must focus heavily on low-power consumption and hardwarelevel optimization. Teams must utilize low-level configurations (such as Direct Memory Access (DMA) and hardware timers) to ensure the processing unit does not drain a marine drone's battery pack while trying to compute complex trigonometric wave values under strict real-time constraints.
•Expected Solution Teams are expected to deliver a functional physical hardware prototype consisting of the following modules:
•Embedded Firmware Engine: A robust program deployed on a physical microcontroller or FPGA (written in C/C++, Verilog, or VHDL). The firmware must utilize hardware timers and DMA to stream wave-generation arrays directly to an internal or external DAC without stalling the CPU. The system must support multiple modulation types on the fly: LFM chirps, geometric sweeps, and phase-coded pulses.
•Environmental Sensor Interface & Adaptation Logic: A physical control interface where real-time environmental changes are introduced to the hardware (via physical sensors, or potentiometers simulating sensors for parameters like 'Entering Muddy Estuary' or 'Entering Clear Shallow Reef'). The microcontroller must read these inputs via an ADC and modify three critical wave parameters instantly:
1.Bandwidth/Center Frequency (Tuning for range vs. resolution)
2.Pulse Duration (Controlling total energy output)
3.Amplitude/Signal Power
•Analog Signal Conditioning & Hardware Filters: A physical analog frontend circuit (built on a breadboard or custom PCB) featuring active/passive low-pass filters and an operational amplifier. Combined with digital windowing filters (such as Hamming, Hann, or Blackman windows) applied in the firmware, this hardware must smooth out sudden voltage jumps at the start and end of a pulse, protecting the transmitter hardware from electrical stress and eliminating sidelobe artifacts.
•Physical Form Factor & Output Validation: The physical analog output of the transmitter payload must be connected to an oscilloscope or spectrum analyzer at the judging table.The generated raw waves must demonstrate clean, low-distortion, mathematically sound spectrograms when validated via a Fast Fourier Transform (FFT). Additionally, the module should be housed in a robust, 3D-printed or fabricated structural enclosure representing a field-deployable payload pod designed for an AUV hull slot.