Guidance Algorithm Simulator

A 2D missile-target engagement simulator implementing four classical guidance laws for interceptor/missile flight path control.

Demo Preview

Guidance Laws Implemented

Law	Full Name	Key Property
PP	Pure Pursuit	Always aims at target — simple, energy-wasteful
PN	Proportional Navigation	Industry standard — proportional to LOS rate
APN	Augmented PN	PN + target acceleration feedforward
CLOS	Command Line-of-Sight	Keeps missile on LOS from launch point

Architecture

src/
├── kinematics.py   # Point-mass Body + maneuvering Target
├── guidance.py     # PP / PN / APN / CLOS guidance laws
├── simulator.py    # Engagement runner (intercept detection, miss distance)
└── visualize.py    # 2D trajectory + miss distance comparison plot
tests/
└── test_guidance.py
docs/
└── guidance_comparison.png

Quick Start

pip install -r requirements.txt
cd src
python visualize.py

Example Output

PurePursuit                    miss=  42.3m  t=MISS
ProportionalNavigation         miss=   4.1m  t=12.34s
AugmentedPN                    miss=   1.8m  t=11.97s
CLOS                           miss=  18.7m  t=MISS

Proportional Navigation

The workhorse of modern missile guidance:

a_cmd = N · Vc · λ̇

where:
  N    = navigation constant (3–5 typical)
  Vc   = closing velocity (m/s)
  λ̇   = LOS angular rate (rad/s)

Applied perpendicular to the line-of-sight, this drives the missile toward a collision triangle geometry — zero-effort miss.

Augmented PN

Extends PN with target acceleration feedforward:

a_cmd = N · Vc · λ̇ + (N/2) · aT⊥

Where aT⊥ is the target acceleration perpendicular to LOS. Significantly improves performance against maneuvering targets.

Running Tests

pytest tests/ -v