Software system for laser targeting dropped ammunition
For last few years usage of small commercial unmanned aerial vehicles (UAV) on battlefield was drastically increased. In addition to use UAVs as spotter, they more and more frequently applied to drop small ammunition on enemy forces. In this paper laser targeting system that suitable for use on ligh...
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pp_isofts_kiev_ua-article-5642024-04-26T21:28:47Z Software system for laser targeting dropped ammunition Програмна система для лазерного керування скиданими боєприпасами Bezpalko, S.O. Shymkovysh, V.M. Kravets, P.I. Novatskyi, A.O. Shymkovysh, L.L. Doroshenko, А.Yu. laser targeting; microcontroller; unmanned aerial vehicles; regulators; hashtags; pulse width modulation; analog digital converter UDC 004.93’1 лазерне націлювання, мікроконтролер, безпілотні літальні апарати, регулятори, широтно-імпульсна модуляція, аналого-цифровий перетворювач УДК 004.93’1 For last few years usage of small commercial unmanned aerial vehicles (UAV) on battlefield was drastically increased. In addition to use UAVs as spotter, they more and more frequently applied to drop small ammunition on enemy forces. In this paper laser targeting system that suitable for use on lightweight, mobile drones that drop freefalling ammunition was developed. Laser targeting systems are used for detecting and tracking the targets in the battlefield by obtaining the position information of these targets which is being designated and illuminated by UAV’s laser designator then the laser light reflected from these targets and come to the input of the optical systems of the dropped ammunition. An optical system for collimating the reflected beam from the target is one of the main components of the laser targeting system (LTS). The Quad Detector (QD) as a part of this optical system is simply consists of four photodiodes capable of detecting light spot projected on its surfaces and determine the deviation position of the laser spot from its center. It converts the incident laser spot to its corresponding photocurrent, the readout circuit that filter and convert the photocurrent to its corresponding voltage and the tracking system that is controlling the laser seeker movement to track the intended target based on the feedback information of the QD depending on the real position of the tracking platform. Developed system will ensure that munitions are accurately hit the target, reducing unnecessary casualties and damage, as well as reducing the number of sorties required and the time spent in hazardous airspace for the unmanned aerial vehicle.Problems in programming 2023; 2: 10-23 Розроблено програмно-апаратний комплекс для лазерної системи керування скиданими боєприпасами, програмне забезпечення для отримання даних з аналогового інфрачервоного датчика, програмну реалізацію каналу зв’язку між базою та боєприпасом, систему отримання та обробки сигналу та цифровий фільтр. Побудовано модель інфрачервоного каналу зв’язку з отримувачем та випромінювачем для проведення тестування створеного рішення. Проаналізувавши типові рішення лазерних систем керування та наклавши на них часові та ресурсні обмеження, було обрано наступні рішення: ШІМ для модуляції сигналу з використання інфрачервоного випромінювача, фільтр Баттерворта для фільтрування даних несучої частоти отриманих даних інфрачервоними фотодіодами. Для реалізації моделі було використано ATmega328p як мікроконтролера, для зчитування аналогового сигналу з давачів, використовуючи вбудований АЦП та для генерації сигналу за допомогою ШІМ. Фотодіоди та світлодіоди інфрачервоного спектру 900нм для передачі і отримання сигналу.Результати тестування дали наступні характеристики розробленого програмногорішення: розмір програми 3406 байт (11% з 30720 байт макс.) мінімальне використання пам’яті: 1337 байт (65% з 2048 байт макс.), частота дискретизації АЦП: 153.8 кГц для одного сенсора або 38.45 кГц для чотирьох, швидкість роботи цифрового фільтру: 1000 циклів за 60200 наносекунд.Prombles in programming 2023; 2: 10-23 Інститут програмних систем НАН України 2023-08-04 Article Article application/pdf https://pp.isofts.kiev.ua/index.php/ojs1/article/view/564 10.15407/pp2023.02.010 PROBLEMS IN PROGRAMMING; No 2 (2023); 10-23 ПРОБЛЕМЫ ПРОГРАММИРОВАНИЯ; No 2 (2023); 10-23 ПРОБЛЕМИ ПРОГРАМУВАННЯ; No 2 (2023); 10-23 1727-4907 10.15407/pp2023.02 en https://pp.isofts.kiev.ua/index.php/ojs1/article/view/564/623 Copyright (c) 2023 PROBLEMS IN PROGRAMMING |
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Problems in programming |
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laser targeting microcontroller unmanned aerial vehicles regulators hashtags pulse width modulation analog digital converter UDC 004.93’1 |
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laser targeting microcontroller unmanned aerial vehicles regulators hashtags pulse width modulation analog digital converter UDC 004.93’1 Bezpalko, S.O. Shymkovysh, V.M. Kravets, P.I. Novatskyi, A.O. Shymkovysh, L.L. Doroshenko, А.Yu. Software system for laser targeting dropped ammunition |
| topic_facet |
laser targeting microcontroller unmanned aerial vehicles regulators hashtags pulse width modulation analog digital converter UDC 004.93’1 лазерне націлювання мікроконтролер безпілотні літальні апарати регулятори широтно-імпульсна модуляція аналого-цифровий перетворювач УДК 004.93’1 |
| format |
Article |
| author |
Bezpalko, S.O. Shymkovysh, V.M. Kravets, P.I. Novatskyi, A.O. Shymkovysh, L.L. Doroshenko, А.Yu. |
| author_facet |
Bezpalko, S.O. Shymkovysh, V.M. Kravets, P.I. Novatskyi, A.O. Shymkovysh, L.L. Doroshenko, А.Yu. |
| author_sort |
Bezpalko, S.O. |
| title |
Software system for laser targeting dropped ammunition |
| title_short |
Software system for laser targeting dropped ammunition |
| title_full |
Software system for laser targeting dropped ammunition |
| title_fullStr |
Software system for laser targeting dropped ammunition |
| title_full_unstemmed |
Software system for laser targeting dropped ammunition |
| title_sort |
software system for laser targeting dropped ammunition |
| title_alt |
Програмна система для лазерного керування скиданими боєприпасами |
| description |
For last few years usage of small commercial unmanned aerial vehicles (UAV) on battlefield was drastically increased. In addition to use UAVs as spotter, they more and more frequently applied to drop small ammunition on enemy forces. In this paper laser targeting system that suitable for use on lightweight, mobile drones that drop freefalling ammunition was developed. Laser targeting systems are used for detecting and tracking the targets in the battlefield by obtaining the position information of these targets which is being designated and illuminated by UAV’s laser designator then the laser light reflected from these targets and come to the input of the optical systems of the dropped ammunition. An optical system for collimating the reflected beam from the target is one of the main components of the laser targeting system (LTS). The Quad Detector (QD) as a part of this optical system is simply consists of four photodiodes capable of detecting light spot projected on its surfaces and determine the deviation position of the laser spot from its center. It converts the incident laser spot to its corresponding photocurrent, the readout circuit that filter and convert the photocurrent to its corresponding voltage and the tracking system that is controlling the laser seeker movement to track the intended target based on the feedback information of the QD depending on the real position of the tracking platform. Developed system will ensure that munitions are accurately hit the target, reducing unnecessary casualties and damage, as well as reducing the number of sorties required and the time spent in hazardous airspace for the unmanned aerial vehicle.Problems in programming 2023; 2: 10-23 |
| publisher |
Інститут програмних систем НАН України |
| publishDate |
2023 |
| url |
https://pp.isofts.kiev.ua/index.php/ojs1/article/view/564 |
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10
Інформаційні системи
Introduction
In the modern world, one of the most
pressing issues is ensuring the security of
national borders and territories. Developing
effective means of defense is a necessary step
in ensuring national security [1-3]. One of the
means of defense that is gaining popularity at
present is the dropping of ordnance that can
destroy a target from a great distance using
lightweight and mobile unmanned aerial
vehicles (UAVs). However, the accuracy
of dropping ordnance and hitting the target
remains a major challenge and is highly
dependent on the skills and abilities of the
operator of the device and weather conditions.
Under these circumstances, the development of
new technologies that can ensure the accuracy
of dropping ordnance is particularly important.
In the civilian sector, freefalling
guided objects control systems can be
used in the delivery industry as a guidance
system for postal drones. Additionally, these
systems can be used in construction for the
precise placement of large building elements
or for assisting in the unloading of goods in
warehouses.
This system will provide accurate
dropping of ordnance and hitting the
target, reducing the number of unnecessary
casualties and damages, as well as reducing
the number of necessary flights and time
spent in hazardous airspace for unmanned
aerial vehicles. The research results can be
useful for military, law enforcement, and
rescue services. In addition, the work can be
used for further improvement of border and
territory protection and safety systems.
Semi-Active Laser Homing (SALH)
was chosen as the targeting method[4-8].
With SALH technique, a laser is directed at
the target, and the laser radiation is reflected
off the target and scattered in all directions
(this is known as «painting the target» or
«laser painting»). The missile, bomb, or
other projectiles are launched or released
somewhere close to the target. When they
are close enough for a portion of the reflected
laser radiation to reach them, a laser receiver
determines the direction from which this
radiation is coming and adjusts the trajectory
of the projectile toward the source. As long
as the projectile remains in the beam, its
УДК 004.93’1 http://doi.org/10.15407/pp2023.02.010
S.O. Bezpalko, V.M. Shymkovysh, P.I. Kravets, A.O. Novatskyi, L.L. Shymkovysh,
А.Yu. Doroshenko
SOFTWARE SYSTEM FOR LASER TARGETING
DROPPED AMMUNITION
For last few years usage of small commercial unmanned aerial vehicles (UAV) on battlefield was
drastically increased. In addition to use UAVs as spotter, they more and more frequently applied to drop
small ammunition on enemy forces. In this paper laser targeting system that suitable for use on lightweight,
mobile drones that drop freefalling ammunition was developed. Laser targeting systems are used for
detecting and tracking the targets in the battlefield by obtaining the position information of these targets
which is being designated and illuminated by UAV’s laser designator then the laser light reflected from
these targets and come to the input of the optical systems of the dropped ammunition. An optical system for
collimating the reflected beam from the target is one of the main components of the laser targeting system
(LTS). The Quad Detector (QD) as a part of this optical system is simply consists of four photodiodes
capable of detecting light spot projected on its surfaces and determine the deviation position of the laser
spot from its center. It converts the incident laser spot to its corresponding photocurrent, the readout
circuit that filter and convert the photocurrent to its corresponding voltage and the tracking system that is
controlling the laser seeker movement to track the intended target based on the feedback information of the
QD depending on the real position of the tracking platform. Developed system will ensure that munitions
are accurately hit the target, reducing unnecessary casualties and damage, as well as reducing the number
of sorties required and the time spent in hazardous airspace for the unmanned aerial vehicle.
Key words: laser targeting, microcontroller, unmanned aerial vehicles, regulators, hashtags, pulse width
modulation, analog digital converter.
© S.O. Bezpalko, V.M. Shymkovysh, P.I. Kravets, A.O. Novatskyi, L.L. Shymkovysh, А.Yu. Doroshenko, 2023
ISSN 1727-4907. Проблеми програмування. 2023. №2
11
Інформаційні системи
trajectory will be corrected towards the target,
providing a high degree of accuracy [9].
For this project infrared (IR) spectrum
was chosen for laser and quad detector as
it is commonly used for such applications.
ATmega328p used as control device for its
characteristics and availability. ATmega328p
has six PWM channels and 6-channel 10-bit
ADC, 2KBytes Internal SRAM, low power
drain(only 0.2mA in active mode and 0.1µA
in power-down mode)[10-15].
The aim of this work is to create
laser targeting system suitable for usage on
lightweight mobile UAVs.
1. Laser control
Laser technology, specifically light
amplification by stimulated emission of
radiation, has revolutionized the accuracy
and effectiveness of modern weaponry.
Laser systems have enabled military forces
to target a wider range of objects with
greater precision and with fewer munitions
than previously possible. However, laser
designators are susceptible to degradation
caused by atmospheric scatter and various
target reflections. To ensure effective use
of laser designators and seekers, a pulse
coding system is employed based on Pulse
Repetition Frequency (PRF)[16].
Example [17] of Pulse Repetition
Frequency signal is shown in Figure 1.
To generate pulse repetition frequency
signal on IR laser we will use pulse-width
modulation (PWM). To create PWM, the
Atmega328 microcontroller has 3 built-in
timers [10, 14, 15]: Timer0, Timer1, and
Timer2. In this project, Timer 0 was used.
The Timer/Counter can operate on
an internal clock pulse, through a frequency
divider, or by using an external clock source
on pin T0. The clock source selection logic
block controls the source and edge that the
Timer/Counter uses to increase (or decrease)
its value. The Timer/Counter is inactive
when no clock signal source is selected. The
output of the clock source selection block is
called the timer clock signal (clkT0) [14].
The dual buffer output compare
registers (OCR0A and OCR0B) are
continuously compared with the value of the
Timer/Counter. The result of the comparison
can be used by the waveform generator to
create PWM or a variable output signal on
the output compare pins (OC0A and OC0B).
The output compare match event also sets
the output compare flag (OCF0A or OCF0B),
which can be used to generate an output
compare interrupt request.
For our application frequency of
PWM signal should be low enough so
analog-to-digital converter can get some
samples to be able to filter signal (with 8
prescaler its 153.8/4 kHz as we will read data
from 4 sensors in QD). But high enough to
be detectable and to not influence speed of
reaction.
On Figure 2 we can see the setup of
PWM for IR laser. This code is configuring
PWM (Pulse Width Modulation) for an IR
emitter on the Atmega328P microcontroller
[18]. Note that _BV(bit) is defined as (1 <<
(bit)).
The code starts by resetting both
timer/counters TCCR0A and TCCR0B to
their default values of zero.
Then, it sets Pin PD5 to output mode
by setting the corresponding bit in the DDRD
register.
After that, it configures TCCR0A and
TCCR0B registers to set the desired PWM
mode and frequency. The TCCR0A register
Figure 1. Pulse Repetition Frequency signal
12
Інформаційні системи
is set to _BV(COM0A1) | _BV(COM0B1)
| _BV(COM0B0) | _BV(WGM01) | _
BV(WGM00), which sets the waveform
generation mode to fast PWM with top value
OCR0A, and sets the Compare Output Mode
to set OC0A/OC0B on Compare Match, clear
OC0A/OC0B at BOTTOM (non-inverting
mode). The default clock source for Timer 0
is the system clock. We can set the prescaler
by modifying CS00, CS01, and CS02 in
TCCR0B [10, 15, 19]. The TCCR0B register
is set to _BV (CS02), which sets the clock
prescaler of 256.
The PWM frequency for the output
can be calculated by the following equation:
where:
• freq: the PWM frequency in Hz;
• f(clkIO): the clock frequency of
the microcontroller in Hz, which is 16MHz
in this case;
• N: the prescaler value used for the
timer, which is 256 in this case
Finally, the OCR0B register is set to
127, which sets the duty cycle of the PWM
signal to 50% (half of the maximum value).
This means the IR emitter will turn on for
half of the PWM cycle and off for the other
half.
Overall, this code sets up the
Atmega328P to generate a ~0.244 kHz PWM
signal with a 50% duty cycle on Pin PD5,
which is connected to an IR emitter.
2. Reading data from photodiodes
While UAV emits infrared laser at
target, dropped ammunition should correct
its trajectory into target. Photodiode sensors
located on ammunition receive reflection of
IR laser from target we need to use analog-
digital-transformation (ADC) to process this
data and calculate vector to target.
To successfully process data, we
should have fast ADC to get a lot of samples
for filtering. Let’s look at ADC in Atmel
microcontrollers. Atmega328p features 10
bit ADC and provides 6 analog pins [10,
14, 15]; meaning you can connect up to 6
different analog devices to microcontroller,
as we will connect IR quad sensor it will use
4 ADC pins and leave 2 pins for some other
use.
On figure 3 we can see ADC setup
on atmega328 for the project. For testing
only one photodiode was used. To process
data, a measurement was stored in 1024
byte array and then was send via serial port
to computer. It was done this way to allow
ADC work at full speed. To save space only
8 bits for each measurement was stored as
it has enough precision to work with data
and saves a lot of memory. This is important
because Atmega328p has only 2kB internal
memory.
First two lines clear the ADCSRA and
ADCSRB registers to ensure that all bits are
initialized to zero before setting any of them.
The ADCSRA register controls the operation
of the ADC, while the ADCSRB register
controls some additional settings that are not
used in this code.
Figure 2. listing of PWM setup code
13
Інформаційні системи
Figure 3. listing of ADC setup code
The 3th line sets the input channel for
the ADC to the ADC0 analog input pin of the
microcontroller. The ADMUX register has
several bits that select the input channel for
the ADC, and this line sets those bits to 0x00
(which is equivalent to setting them to zero
in this case). In the future more inputs will
be used but for initial tests its good enough.
Next line sets the reference voltage for
the ADC to the internal 5V reference voltage.
The REFS0 bit of the ADMUX register is set
to 1 to select the internal reference voltage.
This means that the ADC will measure the
input voltage relative to this 5V reference
voltage. Therefore, using this formula, we
can get voltage value on analog pin:
Where VIN is the voltage on the
selected input pin and VREF the selected
voltage reference. In our case this formula
will look like this, as VREF = 5V and we use
only first 8 bits of ADC:
To conveniently use only 8 bit data,
next line sets the ADC result to be left-
aligned in the ADCH register [20]. The
ADLAR bit of the ADMUX register is set
to 1 to left-align the result. This means that
the 8 most significant bits of the ADC result
will be stored in the ADCH register, and the
2 least significant bits will be stored in the 2
least significant bits of the ADCL register. In
this case all we need to do to get data is read
value in ADCH register.
Figure 4. ADC Timing Diagram, Auto Triggered Conversion Figure 4.
ADC Timing Diagram, Auto Triggered Conversion
14
Інформаційні системи
As was said before, we need to get
enough samples, so 6th line sets the ADC
prescalervalue to 8, which means that the
ADC clock frequency is divided by 8 before
the analog signal is sampled. This line sets
the ADPS1 and ADPS0 bits of the ADCSRA
register to 1, which selects a prescaler value
of 8. Unfortunately, we can’t use lower
prescaler as it would result in unreliable
results. From datasheet [14] we know that
one conversation takes 13 clock cycles
(figure 4).
We can calculate sample rate of ADC
with this formula:
The resulting sampling rate is 153.8
kHz, which is fast enough to capture the
signal from an IR sensor. Next line enables
auto-triggering of the ADC. The ADATE bit
of the ADCSRA register is set to 1 to enable
auto-triggering, which means that the ADC
will start a new conversion automatically
whenever a trigger event occurs. The trigger
event can be a timer overflow, an external
interrupt, or other events that are specified
in the ADCSRB register (which is not used
in this code).
To get data we use interrupts when a
measurement is complete. The ADIE bit of
the ADCSRA register is set to 1 to enable
the ADC interrupt, which will trigger
whenever a conversion is complete. The last
2 lines enables the ADC module and starts
the ADC conversion process. The ADEN
bit of the ADCSRA register is set to 1 to
turn on the ADC module. The ADSC bit of
the ADCSRA register is set to 1 to initiate
a single conversion. Once the conversion
is complete, the ADC interrupt will trigger
to indicate that the result is ready. The next
conversion will be triggered automatically
by the auto-triggering feature, since ADATE
was set to 1 earlier in the code.
Overall, this code sets up the ADC
module of the ATmega328P microcontroller
to read analog signals from the A0 input pin,
with a reference voltage of 5V, a sampling
rate of 153.8 kHz, and auto-triggering
enabled. Interrupts are also enabled to handle
the completion of each conversion. Once
the setup is complete, the ADC module is
enabled and a single conversion is initiated.
Subsequent conversions will be triggered
automatically by the auto-triggering feature.
This code is typically used in applications
that require high-speed analog-to-digital
conversion, such as signal processing or
sensing applications.
To verify that ADC is working
correctly we can compare oscillogram of
photodiode signal and output of Atmega328p.
To filter high frequency noise from sensor
data a simple resistor-capacitor (RC) filter
was used.
To get data that microcontroller sends
via serial port to computer PuTTY was used.
It is a free and open-source terminal emulator,
serial console and network file transfer
application. It supports several network
protocols, including SCP, SSH, Telnet,
rlogin, and raw socket connection. It can
also connect to a serial port [21]. After that
data was proceed with Python script and plot
was build using «matplotlib» [22]. We can
see result on figure 5. Overall plot is similar
to oscillogram, but we got a “cuts” every so
often. They accrued because of using buffer
to store data on microcontroller. Every time
buffer is filled up we send data via serial port
and in this time frame ADC turned off. This
would not be a problem on final model as it
won’t use serial to send data. Otherwise, this
problem can be reduced with more optimized
serial code and with using 2 smaller buffers.
3. Data filter implementation
As was noted in chapter “Laser
control” the UAV’s microcontroller uses
modulation on laser to make signal more
recognizable. Therefore, on controllable
ammunition side we need to read this signal
and decode it. To implement this digital filter
was used. A digital filter is a system that
modifies or analyzes digital signals, such as
audio or images, by removing or amplifying
certain frequencies or components. It is
implemented using digital signal processing
techniques, where the input signal is
sampled at discrete time intervals and the
filter algorithm processes these samples
to produce an output signal. They can be
classified based on their transfer function,
which defines how the filter modifies the
15
Інформаційні системи
input signal. Some common types of digital
filters include finite impulse response (FIR)
filters, infinite impulse response (IIR) filters,
and digital notch filters. Digital filters
have many advantages over their analog
counterparts, including the ability to easily
adjust filter parameters, reduced sensitivity
to environmental noise, and the ability to
implement complex filtering algorithms
using software.
In this project passband Butterworth
filter was used. Butterworth filter is a type
of digital filter that is designed to have a flat
frequency response in the passband and a
monotonic attenuation in the stopband. The
Butterworth filter belongs to the family of
infinite impulse response (IIR) filters and is
characterized by its smoothness and absence
of ripples in the passband. It achieves [23]
this by using a maximally flat magnitude
response (figure 6), which means that the
passband has a uniform gain and the cutoff
frequency is defined as the frequency at
which the magnitude response drops by 3 dB.
Butterworth filters can be designed
for various filter orders, which determines
the steepness of the transition between the
passband and stopband. Higher order filters
have steeper transitions but can suffer from
passband ripple and phase distortion. In
contrast, lower order filters have smoother
responses but may not provide enough
attenuation in the stopband.
The algorithm for finding the
coefficients of a Butterworth filter involves
several steps:
1. Determine the filter order: The filter
order, denoted as n, determines the number
of poles or zeros in the filter. It is determined
based on the required cutoff frequency and
the desired transition bandwidth. A higher-
order filter provides a steeper transition but
requires more complex calculations.
2. Calculate the analog prototype
filter: The analog prototype filter is a
normalized low-pass filter that serves as a
reference for designing the Butterworth filter.
The transfer function of the analog prototype
filter is given by:
where s is the complex frequency
variable, ωc is the cutoff frequency, n is the
filter order, and ε is a constant that determines
the filter’s ripple. For Butterworth filter, ε is
set to 1.
3. Convert the analog prototype filter
to a digital filter: The analog prototype filter
is transformed into a digital filter using a
bilinear transformation, which maps the
s-plane of the analog filter to the z-plane of
Figure 5. ADC output plot
16
Інформаційні системи
the digital filter. The transfer function of the
digital filter is given by:
where B(z) and A(z) are the numerator
and denominator polynomials of the digital
filter, respectively. These polynomials can be
calculated using the following equations:
where βi and αi are coefficients that
depend on the filter order and the bilinear
transformation.
Normalize the digital filter
coefficients: The coefficients of the digital
filter are normalized by dividing them by
A(0), which ensures that the DC gain of
the filter is unity. The resulting coefficients
are then used to implement the Butterworth
filter.
To implement Butterworth filter, we
need to calculate filter coefficients. For this
task MATLAB [24] tools will be used. To
calculate filter firstly we need to do spectral
analysis of the input signal. For this purpose,
was used fast Fourier transform [25] to
perform frequency and power spectrum
analysis of time-domain signals.
For this, firstly, we need to get data
sample from microcontroller. As was
mentioned before just straight forward
dumping of ADC data is not ideal as it
creates artifacts in output data. New highly
efficient code was developed to get around
this issue. To get data from Atmega328p to
computer where it can be processed serial
port was used [26].
This code is for an Atmega328P
microcontroller, and it defines a data buffer, a
counter, two offsets, and a flag to start serial
data transfer. The program reads data from
an analog-to-digital converter (ADC) and
stores it in the buffer. When the buffer is full,
the program swaps the offsets, so that the
serial data transfer starts sending data from
the just-populated buffer. The program then
sets the start flag to true and sends the data in
parts using the Serial.write() function. If the
ADC filled the second buffer while the data
transfer is in progress, the program swaps
the offsets and starts sending data from the
beginning of the buffer again.
The buffer is a continuous array of
bytes, with a length of 2 * buffL, where buffL
is a constant unsigned integer, which can
be changed by user to any value that can be
divided by 8. The program uses two separate
buffers within this array, one for storing data
from the ADC and another for sending data
via serial. The two buffers are distinguished by
their respective offsets, offsetW and offsetR.
The program switches between the two buffers
simply by changing the offset. If offset is 0,
then data[offset + i] uses the first buffer, and
if offset is buffL, then data[offset + i] uses
the second buffer. This allows to do a great
optimization of a code. By switching between
Figure 6. The frequency response plot for Butterworth filter with different order
17
Інформаційні системи
offsets, we use simple numeric operations and
avoid branching in code that influence program
running speed very much. The part constant
defines the size of the data sent in parts and
is set to one-eighth of the buffer size, it used
to transfer data via serial port in smaller parts
what increase stability of output data.
The program uses an interrupt
service routine (ISR) to read data from the
ADC(figure 8). The ISR increments the
counter and writes the data to the buffer.
When the counter reaches the buffer size, the
ISR swaps the offsets, sets the start flag to
true, and triggers the serial data transfer. Tag
[[unlikely]] used here to hint compiler that
this branch is unlikely to happen, as it will
occur only once at buffL times.
The main program loop (figure 9)
checks whether the start flag is true. If so,
it sends the data in parts using the Serial.
write() function. Before sending the data,
it resets the start flag to false, so we avoid
sending same data more than one time. Start
flag will be set by ADC interrupt when it will
fill its buffer. If the ADC has filled the second
buffer while the data transfer is in progress,
the loop swaps the offsets and starts sending
data from the beginning of the buffer again.
Overall, this part of the code reads
data from an ADC and sends it via serial in
parts using a continuous buffer that can be
switched between the ADC buffer and the
serial buffer. The program uses an interrupt
to read data from the ADC and a loop to send
data via serial. The program also handles
buffer overflow and switching between
buffers in a simple and efficient manner.
Using Putty [21] we can receive data
from microcontroller and parse it into array of
discrete data, figure 10. Let’s use MATLAB
to read data from log file and build graph,
figure 11.
Figure 7. Global variables of data transfer code
Figure 8. Interrupt service routine of ADC
18
Інформаційні системи
After getting signal in discrete array
form we can analyze it using Fast Fourier
Transformation (FFT). It is a mathematical
algorithm used to transform time-domain
signals into frequency-domain signals.
It is a widely used technique in signal
processing, image processing, and many
other fields. The FFT algorithm is an efficient
implementation of the Discrete Fourier
Transform (DFT), which is a mathematical
technique that converts a sequence of N
complex numbers into another sequence of
N complex numbers. The DFT is defined by
a set of complex exponential functions, and
it provides a way to analyze the frequency
components of a signal, figure 12. Using
MATLAB, we can easily perform FFT and
build the power spectrum plot, figure 13.
As frequency range we will use values from
0 to 10000. To make power spectrum plot
more readable maximum value if power was
limited by 1000.
We can see 2 main spikes on the start
and end of the spectrum. A Fast Fourier
Transformation (FFT) graph with two spikes,
one at the start of the spectrum and the other
at the end, typically indicates that there is a
periodic component in the input signal. The
spike at the start of the spectrum (i.e., at
frequency 0) indicates the presence of a DC
(direct current) component in the signal. A
DC component represents the average value
of the signal over time, and it is often caused
by a bias or offset in the measurement system.
The spike at the end of the spectrum (i.e., at
the Nyquist frequency) indicates the presence
of a high-frequency periodic component in
the signal. The Nyquist frequency is equal to
half of the sampling rate, and it represents the
maximum frequency that can be accurately
represented in the signal.
To get modulated signal we need
to filter middle frequencies. To generate
bandpass Butterworth filter, we can use
MATLAB’s “butter” function [24]. It takes
as parameters needed order of filter, and
relative cutoff frequencies.
Looking at received graph we can
see that it nicely filters out data on carrier
frequency. Its has longest spikes where
background noise is almost zero and lover
spikes where its high. To make this signal
more readable we can take absolute value
from it, multiply so it more relatable to
input. To make filter more precise we also
can increase order of a filter from 10 to 22.
Butter function returns a and b matrix
that contain coefficients for filter. For an
infinite impulse response (IIR) filter, the
transfer function is not a polynomial, but
a rational function. The Z-transforms of
the input and output signals are related by
where b(i) and a(i) are the filter coefficients.
C++ code for Atmega328 was developed to
implement digital filter that can have any
order and be flexible for any coefficients. On
figure 13 we can see implementation of filter.
This implementation (figure 16)
defines a digital filter class called «Filter»
which implements a finite impulse response
(FIR) filter using an array of coefficients for
Figure 9. Main loop of the program
19
Інформаційні системи
Figure 10. MATLAB command to read data from file and build graph
Figure 11. Plot of signal received from Atmega328
Figure 12. Performing FFT in MATLAB
Figure 13. Power spectrum plot of received signal
20
Інформаційні системи
both the numerator (b) and denominator (a) of
the transfer function. The filter has a constant
order of 5, which means it can only process 5
samples at a time, but this parameter can be
easily changed by user to any needed value.
The implementation uses an input
array (x) to store the previous input samples
and an output array (y) to store the previous
output samples. The process() function takes
in a new input sample, shifts all the existing
samples in the input and output arrays by one
position, and computes the output sample
using the filter’s transfer function. The output
sample is then stored in the output array and
returned as the output of the filter.
The filter’s transfer function is
implemented using a difference equation
in the time domain. The output sample
(yn) is computed as a weighted sum of
the input samples (x) and previous output
samples (y) using the filter’s coefficients
for both numerator (b) and denominator (a).
This implementation assumes that all the
coefficients have already been computed and
assigned to the filter’s coefficient arrays.
Note that the implementation uses
the «memmove()» function to shift the input
and output arrays, it is intended for use in a
memory-constrained environment, but also
it’s a lot faster than manually do shift for
each pair of inputs or outputs. Such saves
allow microcontroller to proceed more data
much faster.
4. System characteristics
Compiled code stats:
1. Program size: 3406 bytes (used
11% of a 30720 byte maximum)
2. Minimum Memory Usage: 1337
bytes (65% of a 2048 byte maximum).
Developed system characteristics:
1. ADC sampling frequency: 153.8
kHz for 1 sensor, 38.45 kHz for quad sensor;
2. Developed filter speed: 1000
samples processed in 60200 nanoseconds.
The results satisfy the technical
requirements that was set before developing
the system.
Conclusions
A In conclusion, the development of a
laser targeting system for dropped ammunition
using the Atmega328p microcontroller,
PWM for IR signal modulation, fast ADC
Figure 14. Generating 10th order Butterworth bandpass filter
Figure 15. Filtering data result (bottom graph)
21
Інформаційні системи
for signal read from photodiode, and digital
filtering techniques has been successfully
implemented. The system demonstrated
reliable and accurate targeting capabilities
for dropped ammunition, which could be used
in various military and civilian applications.
The use of the Atmega328p
microcontroller provided a low-cost and
efficient solution for controlling the system,
while the PWM modulation allowed for
precise control of the IR signal. The fast
ADC was crucial for accurate signal reading
from the photodiode, and the implemented
digital filter improved the accuracy of the
results.
Furthermore, the calculated
Butterworth filter in MATLAB allowed for
the optimization of the filter parameters
and improved the overall performance of
the system. The laser targeting system has
the potential to be further improved and
optimized for specific applications.
Overall, the laser targeting system for
dropped ammunition presented in this paper
provides a promising solution for accurate
and reliable targeting, demonstrating the
potential for future advancements in this
area.
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Received 25.04.2023
Про авторів:
Безпалько Станіслав Олегович,
студент 6 курсу
Національного Технічного Університету
України «КПІ імені Ігоря Сікорського»
https://orcid.org/0000-0001-8550-1792
Шимкович Володимир Миколайович,
кандидат технічних наук,
доцент кафедри інформаційних систем
та технологій
Національного технічного університету
України «КПІ імені Ігоря Сікорського».
Кількість наукових публікацій
в українських виданнях – понад 30.
Кількість наукових публікацій
в зарубіжних виданнях – понад 10.
Індекс Хірша – 4. https://orcid.org/0000-
0003-4014-2786
Новацький Анатолій Олександрович,
кандидат технічних наук,
доцент кафедри інформаційних систем та
технологій
Національного технічного університету
України «КПІ імені Ігоря Сікорського».
Кількість наукових публікацій в україн-
ських виданнях – понад 30.
Кравець Петро Іванович,
кандидат технічних наук,
доцент кафедри інформаційних систем та
технологій
Національного технічного університету
України «КПІ імені Ігоря Сікорського».
Кількість наукових публікацій
в українських виданнях – понад 40.
Кількість наукових публікацій в зарубіж-
них виданнях – понад 10.
Індекс Хірша – 4. https://orcid.org/0000-
0003-4632-9832
Шимкович Любов Леонідівна,
асистент кафедри інформаційних систем
та технологій
Національного технічного університету
України «КПІ імені Ігоря Сікорського».
Кількість наукових публікацій
в українських виданнях – 2.
Кількість наукових публікацій в зарубіж-
них виданнях – 1.
https://orcid.org/0000-0002-1291-0373
Дорошенко Анатолій Юхимович,
доктор фізико-математичних наук,
професор, завідувач відділу теорії
комп’ютерних обчислень,
професор кафедри інформаційних систем
та технологій
Національного технічного університету
України «КПІ імені Ігоря Сікорського».
Кількість наукових публікацій в україн-
ських виданнях – понад 200.
Кількість наукових публікацій в зарубіж-
них виданнях – понад 90.
Індекс Хірша – 6. http://orcid.org/0000-
0002-8435-1451
Місце роботи авторів:
Національний технічний університет
України «Київський політехнічний ін-
ститутімені Ігоря Сікорського», проспект
Берестейський 37 та Інститут програм-
них систем НАН України, 03187, м. Київ,
проспект Академіка Глушкова, 40.
Тел.: (044) 526 3559
E-mail:
stas110922@gmail.com,
v.shymkovych@kpi.ua,
a.novatskyi@kpi.ua,
peter_kravets@yahoo.com,
L.shymkovych@gmail.com,
doroshenkoanatoliy2@gmail.com
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