What is an Adaptive Antenna?

Adaptive antenna (also known as zeroing antenna processor (SNAP)), which can automatically align the antenna's maximum radiation direction to the desired station and zero the antenna pattern's lobe to the interfering station. Interfering with antennas is an effective measure for counter-electron countermeasures from airspace. In structure, it is composed of an antenna array and an adaptive processing system, so it is also called an adaptive array.

Adaptive antenna (also known as zeroing antenna processor (SNAP)), which can automatically align the antenna's maximum radiation direction to the desired station and zero the antenna pattern's lobe to the interfering station. Interfering with antennas is an effective measure for counter-electron countermeasures from airspace. In structure, it is composed of an antenna array and an adaptive processing system, so it is also called an adaptive array.

Chinese name

Adaptive antenna

Foreign name

Adaptive antenna

Adaptive Antenna Application

The adaptive array for receiving can automatically adjust the polarization, minimize the polarization attenuation of the desired signal, automatically adjust the maximum receiving direction to the direction of the desired signal, and can automatically adjust the zero direction to the direction of the interference. It has extremely flexible and reliable anti-interference detection capabilities. The adaptive array for transmission can automatically adjust the pattern to direct energy towards the required spatial angular domain. Due to the above good characteristics, adaptive arrays are widely used in communication, radar, radio astronomy and other fields.

A typical array consists of several cells. By adjusting the amplitude and phase of the excitation of each unit (called complex weighting, and represented by W 1, W 2, ..., W n), the shape of the antenna pattern can be controlled. The adaptive array adjusts the complex weighting of each unit through the adaptive processing system, so as to automatically obtain the required directional characteristics in real time. If the number of array elements is n , the array can resist n -1 interference from different directions, and it is said that the n- element array has n -1 spatial degrees of freedom. Complex weighting circuits usually consist of a tapped delay line and a real multiplier. If the number of taps is m , the complex weighting circuit can form the required complex weighting for m -1 frequencies, and it is said that the delay weights of the m -tap complex weighting circuit have m -1 frequency (or time) degrees of freedom. Therefore, the more interferences are combated and the wider the frequency band, the more complicated the adaptive array structure is.

The adaptive processing system is the heart of the adaptive array. Its function is to adapt to the objective environment and needs, and to give correct control information for complex weighting. The adaptive processing system has two important problems, one is the criterion, and the other is the algorithm.

The goal pursued by the adaptive processing system and how it approaches the goal are called adaptive criteria. Generally, the target can be approximated according to the following meanings: the minimum mean square error criterion, the maximum likelihood ratio criterion, and the maximum signal-to-noise ratio criterion. Guidelines are the starting point for designing adaptive processing systems.

The adaptive process is a process that continuously approaches the target. The path it follows is represented by a mathematical model, called an adaptive algorithm. Gradient-based algorithms are usually used, of which the least mean square error algorithm (ie, LMS algorithm) is particularly commonly used. The adaptive algorithm can be implemented by hardware (processing circuit) or software (program control). The former designs the circuit based on the mathematical model of the algorithm, while the latter compiles the mathematical model of the algorithm into a program and implements it with a computer. There are many kinds of algorithms, and its choice is very important. It determines the performance quality and feasibility of the processing system.

Adaptive Antenna Performance Quality

There are four main aspects of the performance and quality of adaptive arrays. Convergence rate: the speed of the adaptation process; Steady-state misalignment: The gap between the array performance and the optimal limit after the adaptation is completed; Stability: whether the adaptation result is a stable single value; Feasibility: the realization of adaptive Whether the hardware or software can be implemented or the cost is too expensive. These aspects are often contradictory, and a compromise design must be adopted.