With the fast growth of the low-altitude economy, drones are becoming an important force in modern air transport, logistics, security inspection, and emergency rescue.
They are not only new types of smart equipment but also complex systems that combine sensing, computing, control, and communication.
As the core part of flight control, the performance of a drone chip directly affects the drone’s intelligence, control accuracy, battery life, and potential for wider applications.
Working Principle of Drone Chips
The control system of a drone relies on three key processes: data collection, computation and analysis, and control execution. The chip acts as the brain of the drone, managing the entire process from data input to decision output.
1. Data Collection
During flight, the chip receives information from various sensor modules such as gyroscopes, accelerometers, barometers, GPS, magnetometers, cameras, and radars.
These sensors collect real-time data about flight status and the surrounding environment, including attitude angles, acceleration, speed, altitude, direction, and obstacle distance. This information serves as the foundation for the flight control system.
The collected data are usually in the form of analog or discrete signals. The chip’s built-in ADC (Analog-to-Digital Converter) converts them into digital signals for further processing.
2. Data Processing and Control Decisions
After receiving the sensor data, the chip runs a series of control algorithms, such as PID control, MPC, or AI-based adaptive algorithms.
These algorithms calculate control parameters like motor speed and servo angles to keep the drone stable or perform specific maneuvers.
In addition, the chip performs data fusion, combining information from multiple sensors to obtain a more accurate estimate of the drone’s flight state.
3. Execution and Power Optimization
The control commands are output as PWM or other control signals to drive motors and servos, adjusting the drone’s posture and movement.
At the same time, the chip manages power efficiency. Through techniques like Dynamic Voltage and Frequency Scaling (DVFS) and power control strategies, it balances computing performance with energy consumption, extending the drone’s flight time.
Main Types of Drone Chips
According to task complexity, power consumption requirements, and system architecture, drone chips can be classified into several categories: Microcontroller Units (MCU), Microprocessor Units (MPU), Digital Signal Processors (DSP), Application-Specific Integrated Circuits (ASIC), and Field-Programmable Gate Arrays (FPGA).
Each type has its own functions, performance characteristics, and application scenarios, together supporting different levels of drone control.
Microcontroller Unit (MCU)
The Microcontroller Unit (MCU) is the most common control core in drone systems. It is typically used in low-power, low-cost, and compact flight control units. The MCU integrates a CPU, memory, timers, communication interfaces (such as I²C, SPI, and UART), and analog-to-digital converters (ADC), enabling it to independently perform data acquisition, computation, and control signal output.
In drones, MCUs mainly handle basic control tasks such as motor speed regulation, attitude stabilization, sensor data collection, and low-level task management (e.g., LED status control and power monitoring).
Due to its simple architecture and low power consumption, the MCU is well-suited for small consumer drones or educational drones.
For example, many small drone flight control boards use STM32 series MCUs, which can achieve multi-sensor data fusion and real-time attitude calculation while maintaining low power consumption.
Moreover, the high integration of MCUs allows stable operation within compact hardware space, providing drones with reliable real-time control capabilities.
Microprocessor Unit (MPU)
The Microprocessor Unit (MPU) acts as the “central brain” of drones, offering stronger computing power and operating system support. Unlike MCUs, MPUs usually do not integrate memory or peripheral control modules; instead, they rely on external memory and interface chips for expansion, supporting complex computations and multitasking.
In drones, MPUs are mainly responsible for advanced control and image processing tasks. They can run operating systems such as Linux or RTOS, performing complex operations including flight path planning, object recognition, obstacle avoidance, map construction, and communication protocol parsing. This high computing capability makes MPUs ideal for industrial-grade and professional drones, such as surveying, inspection, or heavy-lift drones.
Additionally, MPUs often work together with GPUs or AI accelerators, forming a heterogeneous computing architecture that enables drones to perform intelligent image recognition and decision-making. Although MPUs consume more power, they are essential components for drones aiming for higher levels of intelligence and automation.
Digital Signal Processor (DSP)
The Digital Signal Processor (DSP) is designed for high-speed signal computation and real-time data analysis. Its architecture features parallel instruction execution, fast multiply-accumulate (MAC) operations, and pipeline processing, making it ideal for processing continuous signals such as audio, images, and radar data.
In drones, DSPs are used for signal analysis and feature extraction.
For instance, in vision-based drones, DSPs handle image filtering, edge detection, and object recognition, while in radar-based drones, they perform signal preprocessing, echo analysis, and target tracking. The high-speed processing capability of DSPs effectively reduces the load on the main control unit and improves overall system responsiveness.
DSPs can also work in coordination with the MPU through dedicated bus interfaces, forming a dual-core system for control and signal processing. Such an architecture is commonly found in high-precision mapping or security drones, where it enables image fusion, positioning correction, and data compression.
ASIC and FPGA
As drone intelligence continues to advance, Application-Specific Integrated Circuits (ASICs) and Field-Programmable Gate Arrays (FPGAs) have become key technologies in high-performance drone systems.
ASICs are custom-designed chips tailored for specific applications. They can hardwire algorithms directly into the hardware, achieving higher efficiency and lower power consumption under the same computing capability.
For example, in visual recognition or AI inference tasks, ASICs can accelerate Convolutional Neural Network (CNN) computations, enabling drones to perform real-time recognition and autonomous decision-making. ASICs are often used in military or high-end industrial drones, where large-scale production and long-term stability are required.
FPGAs, on the other hand, provide flexibility through reconfigurable hardware. Engineers can use Hardware Description Languages (HDL) to define circuit logic dynamically, making them ideal for rapid algorithm validation and custom data path design. With strong parallel processing capability, FPGAs are widely used for real-time data fusion, sensor synchronization, and high-speed communication protocol handling.
In system integration, ASICs offer efficient, stable solutions for mass production, while FPGAs serve as an ideal platform for early-stage development and algorithm optimization.
Ande Electronics: Driving UAV Innovation with Chip Solutions
Ande Electronics has been deeply engaged in the UAV technology field, dedicated to providing comprehensive support for various types of drone chips to help customers achieve full-chain performance optimization—from basic control to intelligent decision-making. Based on different task complexities, power consumption requirements, and system architectures, Ande offers a wide range of chip solutions and technical support, including MCU, MPU, DSP, ASIC, and FPGA, to meet the control and computing needs of drones at multiple levels.
For lightweight and high-efficiency applications, Ande Electronics provides low-power, highly integrated MCU solutions. For industrial-grade drones that require complex algorithm processing and image recognition, Ande offers high-performance MPU and DSP chips to support real-time path planning, obstacle avoidance, and multi-sensor data fusion. Meanwhile, for high-performance UAV systems with customized needs, Ande also provides ASIC and FPGA solutions to enable algorithm acceleration, parallel signal processing, and hardware-level optimization.
Relying on a stable supply chain and professional technical services, Ande Electronics not only delivers high-quality chip products but also provides full-process support in component selection, system design, and performance optimization. Through flexible inventory management and rapid delivery mechanisms, Ande helps UAV manufacturers accelerate product iteration and technology implementation, driving the intelligent upgrading of drones across mapping, inspection, logistics, and security fields.
