Automobile anti-collision system based on nRF24E1 and TMC2023

Abstract: This paper introduces the performance characteristics of the most popular single-chip RF transceiver chip nRF24E1 and the special chip TMC2023 with related computing functions; explains the related computing theory in signal processing, and combines this theory with the circuit with the above two chips as the core, which is used in the automobile anti-collision system to enhance the ability of the automobile anti-collision system.

introduction

With the development of the times and the progress of society, more and more cars have entered ordinary people's homes. Although road conditions are constantly improving, the current situation of car congestion on the road cannot be avoided. Coupled with the gradual increase in vehicle speeds, vicious traffic accidents occur all the time, causing huge losses of life and property to people and society. Figure 1 The car anti-collision system is a detection device that can send audio-visual warning signals to the driver in advance. It is usually installed on the car and can detect pedestrians, vehicles or surrounding obstacles that attempt to approach the car body; it can send a signal to the driver and passengers in advance that a collision is imminent, prompting the driver or even the driver to take emergency measures to deal with special dangers and avoid losses. At present, although all countries are studying anti-collision systems, how to better solve the problem of false alarms has always troubled relevant workers. Through a large number of experimental studies, international researchers have reached a consensus that if the anti-collision system wants to effectively solve the above problems, it must have the following functions, namely:

① Angle measurement capability is required. The target’s azimuth information is essential for eliminating false alarms.

② Design a complex transmission signal that is easy to generate and has strong anti-interference performance, and combine it with real-time and efficient signal processing and target detection algorithms to eliminate false alarms.

Only when the above two points are closely combined can the reliability of the automobile anti-collision system be guaranteed.

1. Introduction to Chip Features

(1) Related computing chip TMC2032

TMC2032 is a new type of all-digital correlator circuit, with programmable correlation word length and correlation threshold. This chip is a single-chip 64-bit CMOS all-digital correlation large-scale integrated circuit launched by TRW in the United States in recent years. It has three eight-bit shift registers with independent clocks: random data register A, local code register B and mask code register M; 1 seven-bit BCD encoding output, which is compared with the preset threshold value in the comparator. If the correlation value is greater than or equal to the threshold value, the flag bit changes from low to high. Due to the use of advanced high-CMOS production technology, the parallel correlation rate is as high as 30Mbps or more; it can be widely used in synchronization, matched filtering, error detection, recording and barcode recognition, etc., especially suitable for radar signal recognition.

(2) RF transceiver chip nRF24E1

nRF24E1 is a wireless RF transceiver chip with an operating frequency of up to 2.4GHz. It is embedded with a microprocessor compatible with 8051 and a 10-bit 9-input A/D converter, which can work stably at a voltage between 1.9 and 3.6V. It also has a voltage regulator and VDD voltage monitoring, a channel shaping time of less than 200μs, a data rate of 1Mbps, and does not require an external SAW filter. nRF24E1 is the world's first global 2.4GHz universal, complete low-cost RF system-level chip. The wireless transceiver part has the same function as nRF2401. This function is started by an external parallel port and an external SPI. Each signal to be sent can be programmed as an interrupt for the processor, or implemented through the GPIO port. nRF24E1 is a chip that can realize wireless communication within the world's public frequency band range (2.4~2.5GHz). The transceiver contains a fully integrated divider, amplifier, regulator and 2 transceiver units. The output energy, frequency band and other RF parameters can be easily programmed and adjusted through the RF register. In transmit mode, the current consumption is only 10.5mA; in receive mode, it is only 18mA, so the power consumption is quite low.

2 System Structure

The entire information collection system consists of five sets of RF transmitting and receiving devices. The basic circuits of each transmitting and receiving part are the same. Figure 1 is the core circuit of RF transceiver. These five transceiver systems are connected to the DSP central processor. The central processor is responsible for calculating the data transmitted by them, and then making decisions based on the actual situation.

The structure of each transmitting and receiving device is shown in Figure 1. First, the RF transmitting circuit with nRF24E1 as the core emits high-frequency electromagnetic waves. Before the transmission, the modulation signal sent by the related operation chip TMC2032 modulates it, thereby generating a radio frequency signal different from other RF transceiver units, making full preparations for reception. In order to make the electromagnetic wave signal have a sufficiently long propagation distance, the modulated signal needs to be amplified. The circuit that completes this function is the power amplifier circuit. Finally, such a signal is transmitted into the air.

When the electromagnetic waves sent out encounter obstacles and return, they must first be identified by the relevant computing chip TMC2032: if they are sent out by the same group of transmitting parts, they will be received and the signal will be further transmitted to the RF receiving part. The receiving chip calculates the time consumed by the electromagnetic waves through the phase shift generated by the propagation of such electromagnetic waves in the air, and then calculates the distance between the obstacle and the group of transceivers. Finally, this distance information is sent to the central processing unit. The central processing microcontroller must simultaneously calculate the distance information transmitted by 5 groups of RF transceiver units to obtain the three-dimensional azimuth distance between the measured obstacle and the car. At this point, the information collection work of the obstacle has basically been completed, and the remaining is to transmit this comprehensive information to the more advanced central processing unit to let it make the final decision.

3. Layout of transceiver units and calculation examples

Because the obstacle in front of the car must be able to determine its spatial three-dimensional orientation relative to the car during driving, so as to avoid the obstacles in front, behind, left, right, and up and down; and the obstacles in the back only need to determine the distance between them and the car. Therefore, three RF transceiver systems are installed in the front of the car, and the three transceiver systems are distributed in a triangle perpendicular to the horizontal plane; two RF transceiver systems are installed in the back, distributed horizontally. The installation of the entire transceiver system is shown in Figure 2. Figure 3 shows a simple process of calculating the obstacle distance using the RF transceiver system.

The distance calculation diagram of the three-dimensional obstacle composed of S1, S2, S3, T1, T2, and T3 is shown in Figure 3. Among them, points A, B, and C represent the three ultrasonic sensors installed in front of the vehicle, and point E represents the obstacle; EF represents the distance from point E to the horizontal plane, FG represents the distance from the obstacle to the vehicle, and AG represents the distance from the obstacle to the side of the vehicle. What we need are the three straight lines EF, FG, and AG. The solution is as follows:

In △ABC, draw BD⊥AC, connect ED and FD, and we can find

Substituting the known numbers S1, S2, S3, T1, T2, and T3 respectively, we can obtain the three required distance values.

4 Related Algorithms

With the widespread application of radio frequency technology in daily life, people gradually find that radio frequency ranging has certain defects: ① The effective range is relatively short, and increasing the measurement distance by simply increasing the transmission power is very limited; ② The ranging accuracy mainly depends on the signal-to-noise ratio of the echo signal. Under a certain signal-to-noise ratio, improving the measurement accuracy by simply increasing the gain of the pre-amplifier circuit is also very limited. In order to solve the above problems, this car collision avoidance system envisions a radio frequency transmission and receiving system based on pseudo-code modulation.

The random process is white noise, and its instantaneous value obeys Gaussian distribution (normal distribution). Its power spectrum density is uniform in a wide frequency band, and the autocorrelation function has the shape of a delta function. Although the pseudo-random code has only two levels, it has correlation characteristics similar to white noise, but its amplitude probability distribution no longer obeys Gaussian distribution. Therefore, the pseudo-random code can be described by the balance characteristics, run characteristics, and correlation characteristics of the pseudo-random sequence. Pseudo-random coding is implemented by logical operations, and the autocorrelation function of the signal satisfies:

It can be seen that when P is large enough, the autocorrelation coefficient has a sharp two-level characteristic, close to the delta function. In the ultrasonic ranging based on pseudo-random code, the sharp characteristics of the pseudo-code autocorrelation function are used to measure the delay between the transmitted code and the received code, thereby improving the measurement accuracy. The m-sequence pseudo-random code is a sequence with the longest period generated by a linear shift register. Due to its excellent correlation characteristics and easy generation, it has been widely used.

According to the definition of the correlation function, suppose there are two time functions X1(t) and X2(t), then

It is called the autocorrelation function of X1(t);

It is called the cross-correlation function of X1(t) and X2(t).

There are two types of problems in signal detection theory: one is to detect the signal, that is, to judge whether there is a signal based on the received mixed signal (signal plus noise or pure noise); the other is to estimate the parameters, that is, to estimate certain parameters of the signal (such as amplitude, phase, frequency, pulse amplitude, etc.) or waveform based on the detected signal. In order to improve the anti-interference performance, it is necessary to find the best method to receive the signal under interference conditions. Since the correlation function of the periodic signal is still a periodic function, while the correlation function of the interference noise is a delta function. According to these differences, the correlator can be used to detect the periodic signal mixed in the noise interference. This method of detecting the signal by using the difference in time domain characteristics is called the correlation reception method. According to the reference signal, it is divided into the autocorrelation reception method and the cross-correlation reception method. The autocorrelation reception method is to use the autocorrelator to perform the autocorrelation function operation on the input waveform (or data) when the input waveform (or data) cannot be known; the cross-correlation reception method is to use the correlator to perform the cross-correlation function operation on the input waveform (or data) and the local signal when the reference signal can be determined. In this design, the reference signal is the local code, so the cross-correlation reception method is used. In the radio frequency ranging system, it is necessary not only to detect the presence of the echo signal, but also to accurately measure the delay between the echo signal and the transmitted signal. In this way, the time taken for the radio wave to propagate can be accurately known, and then the distance between the obstacle and the car can be calculated.

5 Conclusion

This paper successfully uses advanced radio frequency technology and stable and reliable related algorithms to make the car have strong anti-collision ability. The above overall design scheme has been implemented on the experimental car, and to a certain extent can solve the two key problems that have always troubled relevant workers in the car anti-collision system mentioned above. That is, it has a more sensitive angle measurement ability and a stronger anti-interference ability, which can make the car have a stronger anti-collision ability. Nevertheless, because the life safety of people is related to the driving process of the car, its performance needs to be further improved to enhance the absolute safety of the entire system and then promote it.